2016
|
Devices and methods for power consumption control in powerline communications systems and apparatus Patent Lydi Smaini; Alexandre Rouxel 2016, (Pre SFI). @patent{Smaini2016,
title = {Devices and methods for power consumption control in powerline communications systems and apparatus},
author = {Lydi Smaini and Alexandre Rouxel},
year = {2016},
date = {2016-08-02},
abstract = {The present disclosure includes systems and techniques relating to power line communications (PLC) systems and apparatus. In some implementations, a method includes determining information regarding a potential data rate to be used with a powerline communications (PLC) channel, reducing a bias current or voltage of an analog front end of a PLC transceiver based on the determined information to reduce power consumption of the analog front end of the PLC transceiver, and transmitting or receiving data over the PLC channel with the reduced bias current or voltage of the analog front end of the PLC transceiver.},
note = {Pre SFI},
keywords = {Communications systems, Power consumption},
pubstate = {published},
tppubtype = {patent}
}
The present disclosure includes systems and techniques relating to power line communications (PLC) systems and apparatus. In some implementations, a method includes determining information regarding a potential data rate to be used with a powerline communications (PLC) channel, reducing a bias current or voltage of an analog front end of a PLC transceiver based on the determined information to reduce power consumption of the analog front end of the PLC transceiver, and transmitting or receiving data over the PLC channel with the reduced bias current or voltage of the analog front end of the PLC transceiver. |
| A survey of active learning in collaborative filtering recommender systems Journal Article Mehdi Elahi; Francesco Ricci; Neil Rubens In: Computer Science Review, vol. 20, pp. 29-50, 2016, (Pre SFI). @article{Elahi2016,
title = {A survey of active learning in collaborative filtering recommender systems},
author = {Mehdi Elahi and Francesco Ricci and Neil Rubens},
url = {https://reader.elsevier.com/reader/sd/pii/S1574013715300150?token=EA12A462FC07F42733F4F13375217A57D3FDC7F6047C133156CB1F4E4487DF24C5366547DF4530A25942F690233F2E30},
doi = {10.1016/j.cosrev.2016.05.002},
year = {2016},
date = {2016-06-02},
journal = {Computer Science Review},
volume = {20},
pages = {29-50},
abstract = {In collaborative filtering recommender systems user’s preferences are expressed as ratings for items, and each additional rating extends the knowledge of the system and affects the system’s recommendation accuracy. In general, the more ratings are elicited from the users, the more effective the recommendations are. However, the usefulness of each rating may vary significantly, i.e., different ratings may bring a different amount and type of information about the user’s tastes. Hence, specific techniques, which are defined as “active learning strategies”, can be used to selectively choose the items to be presented to the user for rating. In fact, an active learning strategy identifies and adopts criteria for obtaining data that better reflects users’ preferences and enables to generate better recommendations.
So far, a variety of active learning strategies have been proposed in the literature. In this article, we survey recent strategies by grouping them with respect to two distinct dimensions: personalization, i.e., whether the system selected items are different for different users or not, and, hybridization, i.e., whether active learning is guided by a single criterion (heuristic) or by multiple criteria. In addition, we present a comprehensive overview of the evaluation methods and metrics that have been employed by the research community in order to test active learning strategies for collaborative filtering. Finally, we compare the surveyed strategies and provide guidelines for their usage in recommender systems.},
note = {Pre SFI},
keywords = {Active Learning, Cold Start, Collaborative filtering, New Start, New User, Preference Elicitation, Rating Elicitation, Recommender system, WP2: User Modeling Personalization and Engagement},
pubstate = {published},
tppubtype = {article}
}
In collaborative filtering recommender systems user’s preferences are expressed as ratings for items, and each additional rating extends the knowledge of the system and affects the system’s recommendation accuracy. In general, the more ratings are elicited from the users, the more effective the recommendations are. However, the usefulness of each rating may vary significantly, i.e., different ratings may bring a different amount and type of information about the user’s tastes. Hence, specific techniques, which are defined as “active learning strategies”, can be used to selectively choose the items to be presented to the user for rating. In fact, an active learning strategy identifies and adopts criteria for obtaining data that better reflects users’ preferences and enables to generate better recommendations.
So far, a variety of active learning strategies have been proposed in the literature. In this article, we survey recent strategies by grouping them with respect to two distinct dimensions: personalization, i.e., whether the system selected items are different for different users or not, and, hybridization, i.e., whether active learning is guided by a single criterion (heuristic) or by multiple criteria. In addition, we present a comprehensive overview of the evaluation methods and metrics that have been employed by the research community in order to test active learning strategies for collaborative filtering. Finally, we compare the surveyed strategies and provide guidelines for their usage in recommender systems. |
| The enrichment of lexical resources through incremental parsebanking Journal Article V Rosén; M Thunes; P Haugereid; GS Losnegaard; H Dyvik; P Meurer; G Lyse; Koenraad De Smedt In: 2016, (Pre SFI). @article{Rosén2016,
title = {The enrichment of lexical resources through incremental parsebanking},
author = {V Rosén and M Thunes and P Haugereid and GS Losnegaard and H Dyvik and P Meurer and G Lyse and Koenraad De Smedt},
url = {https://bora.uib.no/bora-xmlui/handle/1956/15680},
year = {2016},
date = {2016-06-01},
note = {Pre SFI},
keywords = {WP5: Norwegian Language Technologies},
pubstate = {published},
tppubtype = {article}
}
|
| Alleviating the new user problem in collaborative filtering by exploiting personality information Journal Article Ignacio Fernandez Tobias; Matthias Braunhofer; Mehdi Elahi; Francesco Ricci; Ivan Cantador In: User Modeling and User-Adapted Interaction, vol. 26, no. 2-3, pp. 221-255, 2016, (Pre SFI). @article{Tobias2016,
title = {Alleviating the new user problem in collaborative filtering by exploiting personality information},
author = {Ignacio Fernandez Tobias and Matthias Braunhofer and Mehdi Elahi and Francesco Ricci and Ivan Cantador},
url = {https://www.researchgate.net/publication/285574429_Alleviating_the_New_User_Problem_in_Collaborative_Filtering_by_Exploiting_Personality_Information},
doi = {10.1007/s11257-016-9172-z},
year = {2016},
date = {2016-06-01},
journal = {User Modeling and User-Adapted Interaction},
volume = {26},
number = {2-3},
pages = {221-255},
abstract = {The new user problem in recommender systems is still challenging, and there is not yet a unique solution that can be applied in any domain or situation. In this paper we analyze viable solutions to the new user problem in collaborative filtering (CF) that are based on the exploitation of user personality information: (a) personality-based CF, which directly improves the recommendation prediction model by incorporating user personality information, (b) personality-based active learning, which utilizes personality information for identifying additional useful preference data in the target recommendation domain to be elicited from the user, and (c) personality-based cross-domain recommendation, which exploits personality information to better use user preference data from auxiliary domains which can be used to compensate the lack of user preference data in the target domain. We benchmark the effectiveness of these methods on large datasets that span several domains, namely movies, music and books. Our results show that personality-aware methods achieve performance improvements that range from 6 to 94 % for users completely new to the system, while increasing the novelty of the recommended items by 3–40 % with respect to the non-personalized popularity baseline. We also discuss the limitations of our approach and the situations in which the proposed methods can be better applied, hence providing guidelines for researchers and practitioners in the field.},
note = {Pre SFI},
keywords = {Active Learning, Cold-start, Collaborative filtering, Cross-domain, Recommender systems, User Personality, WP2: User Modeling Personalization and Engagement},
pubstate = {published},
tppubtype = {article}
}
The new user problem in recommender systems is still challenging, and there is not yet a unique solution that can be applied in any domain or situation. In this paper we analyze viable solutions to the new user problem in collaborative filtering (CF) that are based on the exploitation of user personality information: (a) personality-based CF, which directly improves the recommendation prediction model by incorporating user personality information, (b) personality-based active learning, which utilizes personality information for identifying additional useful preference data in the target recommendation domain to be elicited from the user, and (c) personality-based cross-domain recommendation, which exploits personality information to better use user preference data from auxiliary domains which can be used to compensate the lack of user preference data in the target domain. We benchmark the effectiveness of these methods on large datasets that span several domains, namely movies, music and books. Our results show that personality-aware methods achieve performance improvements that range from 6 to 94 % for users completely new to the system, while increasing the novelty of the recommended items by 3–40 % with respect to the non-personalized popularity baseline. We also discuss the limitations of our approach and the situations in which the proposed methods can be better applied, hence providing guidelines for researchers and practitioners in the field. |
| NorGramBank: A 'Deep' Treebank for Norwegian.Proceedings of LREC Proceeding H Dyvik; P Meurer; V Rosén; Koenraad De Smedt; P Haugereid; GS Losnegaard; G Lyse; M Thunes 2016, (Pre SFI). @proceedings{Dyvik2016,
title = {NorGramBank: A 'Deep' Treebank for Norwegian.Proceedings of LREC},
author = {H Dyvik and P Meurer and V Rosén and Koenraad De Smedt and P Haugereid and GS Losnegaard and G Lyse and M Thunes},
url = {https://www.aclweb.org/anthology/L16-1565.pdf},
year = {2016},
date = {2016-05-16},
note = {Pre SFI},
keywords = {WP5: Norwegian Language Technologies},
pubstate = {published},
tppubtype = {proceedings}
}
|
| Data-independent sequencing with the timing object: a JavaScript sequencer for single-device and multi-device web media. In Proceedings of the 7th International Conference on Multimedia Systems (MMSys '16) Proceeding Ingar Mæhlum Arntzen; Njål Borch 2016, (Pre SFI). @proceedings{Arntzen2016,
title = {Data-independent sequencing with the timing object: a JavaScript sequencer for single-device and multi-device web media. In Proceedings of the 7th International Conference on Multimedia Systems (MMSys '16)},
author = {Ingar Mæhlum Arntzen and Njål Borch},
url = {https://www.w3.org/community/webtiming/files/2016/05/mmsys2016slides.pdf},
year = {2016},
date = {2016-05-12},
note = {Pre SFI},
keywords = {WP4: Media Content Interaction and Accessibility},
pubstate = {published},
tppubtype = {proceedings}
}
|
| Hapticolor: Interpolating color information as haptic feedback to assist the colorblind Proceeding M.G Carcedo; S.H Chua; S Perrault; P Wozniak; R Joshi; M Obaid; Morten Fjeld; S Zhao 2016, (Pre SFI). @proceedings{Carcedo2016,
title = {Hapticolor: Interpolating color information as haptic feedback to assist the colorblind},
author = { M.G Carcedo and S.H Chua and S Perrault and P Wozniak and R Joshi and M Obaid and Morten Fjeld and S Zhao},
url = {https://dl.acm.org/doi/10.1145/2858036.2858220
https://www.youtube.com/watch?v=qjoH6eNNZBU},
year = {2016},
date = {2016-05-01},
note = {Pre SFI},
keywords = {WP4: Media Content Interaction and Accessibility},
pubstate = {published},
tppubtype = {proceedings}
}
|
| RAMPARTS: Supporting sensemaking with spatially-aware mobile interactions Journal Article P Wozniak; N. Goyal; P. Kucharski; L. Lischke; S. Mayer; Morten Fjeld In: 2016, (Pre SFI). @article{Wozniak2016,
title = { RAMPARTS: Supporting sensemaking with spatially-aware mobile interactions},
author = {P Wozniak and N. Goyal and P. Kucharski and L. Lischke and S. Mayer and Morten Fjeld},
url = {https://dl.acm.org/doi/10.1145/2858036.2858491
https://www.youtube.com/watch?v=t01yLj3xhVc},
year = {2016},
date = {2016-05-01},
note = {Pre SFI},
keywords = {WP4: Media Content Interaction and Accessibility},
pubstate = {published},
tppubtype = {article}
}
|
| MWEs in Treebanks: From Survey to Guidelines Proceeding V Rosén; Koenraad De Smedt; GS Losnegaard; E Bejcek; A Savary; P Osenova 2016, (Pre SFI). @proceedings{Rosén2016b,
title = {MWEs in Treebanks: From Survey to Guidelines},
author = {V Rosén and Koenraad De Smedt and GS Losnegaard and E Bejcek and A Savary and P Osenova},
url = {https://www.aclweb.org/anthology/L16-1368.pdf},
year = {2016},
date = {2016-05-01},
note = {Pre SFI},
keywords = {WP5: Norwegian Language Technologies},
pubstate = {published},
tppubtype = {proceedings}
}
|
| Universal dependencies for Norwegian Proceeding Lilja Øvrelid; P Hohle 2016, (Pre SFI). @proceedings{Øvrelid2016,
title = { Universal dependencies for Norwegian},
author = {Lilja Øvrelid and P Hohle},
url = {https://www.aclweb.org/anthology/L16-1250/},
year = {2016},
date = {2016-05-01},
note = {Pre SFI},
keywords = {WP5: Norwegian Language Technologies},
pubstate = {published},
tppubtype = {proceedings}
}
|
| “Practicing Audience-Centred Journalism Research.” Book Chapter Irene Costera Meijer In: Witschge, T.; Anderson, C. W.; Domingo, D.; Hermida, A. (Ed.): Chapter 36, pp. 546-561, Sage, 55 City Road, London, 2016, ISBN: 9781473906532, (Pre SFI). @inbook{Meijer2016,
title = {“Practicing Audience-Centred Journalism Research.” },
author = {Irene Costera Meijer},
editor = {T. Witschge and C.W. Anderson and D. Domingo and A. Hermida},
url = {https://sk.sagepub.com/Reference/the-sage-handbook-of-digital-journalism/i3760.xml},
doi = {10.4135/9781473957909.n36},
isbn = {9781473906532},
year = {2016},
date = {2016-01-01},
pages = {546-561},
publisher = {Sage},
address = {55 City Road, London},
chapter = {36},
abstract = {The production and consumption of news in the digital era is blurring the boundaries between professionals, citizens and activists. Actors producing information are multiplying, but still media companies hold central position. Journalism research faces important challenges to capture, examine, and understand the current news environment. The SAGE Handbook of Digital Journalism starts from the pressing need for a thorough and bold debate to redefine the assumptions of research in the changing field of journalism. The 38 chapters, written by a team of global experts, are organised into four key areas: Section A: Changing Contexts Section B: News Practices in the Digital Era Section C: Conceptualizations of Journalism Section D: Research Strategies By addressing both institutional and non-institutional news production and providing ample attention to the question 'who is a journalist?' and the changing practices of news audiences in the digital era, this Handbook shapes the field and defines the roadmap for the research challenges that scholars will face in the coming decades.},
note = {Pre SFI},
keywords = {Journalism, News, WP1: Understanding Media Experiences},
pubstate = {published},
tppubtype = {inbook}
}
The production and consumption of news in the digital era is blurring the boundaries between professionals, citizens and activists. Actors producing information are multiplying, but still media companies hold central position. Journalism research faces important challenges to capture, examine, and understand the current news environment. The SAGE Handbook of Digital Journalism starts from the pressing need for a thorough and bold debate to redefine the assumptions of research in the changing field of journalism. The 38 chapters, written by a team of global experts, are organised into four key areas: Section A: Changing Contexts Section B: News Practices in the Digital Era Section C: Conceptualizations of Journalism Section D: Research Strategies By addressing both institutional and non-institutional news production and providing ample attention to the question 'who is a journalist?' and the changing practices of news audiences in the digital era, this Handbook shapes the field and defines the roadmap for the research challenges that scholars will face in the coming decades. |
| VizRec: Recommending Personalized Visualizations Journal Article Belgin Mutlu; Eduardo Veas; Christoph Trattner In: ACM Transactions on Interactive Intelligent Systems (TiiS), vol. 6, no. 4, pp. 1-40, 2016, (Pre SFI). @article{Mutlu2016,
title = {VizRec: Recommending Personalized Visualizations},
author = {Belgin Mutlu and Eduardo Veas and Christoph Trattner},
url = {https://www.christophtrattner.info/pubs/ACM-TIIS.pdf},
year = {2016},
date = {2016-01-01},
journal = {ACM Transactions on Interactive Intelligent Systems (TiiS)},
volume = {6},
number = {4},
pages = {1-40},
abstract = {Visualizations have a distinctive advantage when dealing with the information overload problem: since they
are grounded in basic visual cognition, many people understand them. However, creating the appropriate
representation requires specific expertise of the domain and underlying data. Our quest in this paper is to
study methods to suggest appropriate visualizations autonomously. To be appropriate, a visualization has
to follow studied guidelines to find and distinguish patterns visually, and encode data therein. Thus, a
visualization tells a story of the underlying data; yet, to be appropriate, it has to clearly represent those aspects
of the data the viewer is interested in. Which aspects of a visualization are important to the viewer? Can
we capture and use those aspects to recommend visualizations? This paper investigates strategies to
recommend visualizations considering different aspects of user preferences. A multi-dimensional scale is used to
estimate aspects of quality for charts for collaborative filtering. Alternatively, tag vectors describing charts
are used to recommend potentially interesting charts based on content. Finally, a hybrid approach combines
information on what a chart is about (tags) and how good it is (ratings). We present the design principles
behind VizRec, our visual recommender. We describe its architecture, the data acquisition approach with a
crowd sourced study, and the analysis of strategies for visualization recommendation.},
note = {Pre SFI},
keywords = {CCS Concepts, Collaborative filtering;, Content ranking, Human-centered computing, Information Systems, Personalization},
pubstate = {published},
tppubtype = {article}
}
Visualizations have a distinctive advantage when dealing with the information overload problem: since they
are grounded in basic visual cognition, many people understand them. However, creating the appropriate
representation requires specific expertise of the domain and underlying data. Our quest in this paper is to
study methods to suggest appropriate visualizations autonomously. To be appropriate, a visualization has
to follow studied guidelines to find and distinguish patterns visually, and encode data therein. Thus, a
visualization tells a story of the underlying data; yet, to be appropriate, it has to clearly represent those aspects
of the data the viewer is interested in. Which aspects of a visualization are important to the viewer? Can
we capture and use those aspects to recommend visualizations? This paper investigates strategies to
recommend visualizations considering different aspects of user preferences. A multi-dimensional scale is used to
estimate aspects of quality for charts for collaborative filtering. Alternatively, tag vectors describing charts
are used to recommend potentially interesting charts based on content. Finally, a hybrid approach combines
information on what a chart is about (tags) and how good it is (ratings). We present the design principles
behind VizRec, our visual recommender. We describe its architecture, the data acquisition approach with a
crowd sourced study, and the analysis of strategies for visualization recommendation. |
2015
|
| Mediasync Report 2015: Evaluating timed playback of HTML5 Media Journal Article Njål Borch; Ingar Mæhlum Arntzen In: Norut, 2015, ISBN: 978-82-7492-319-5, (Pre SFI). @article{Borch2015b,
title = {Mediasync Report 2015: Evaluating timed playback of HTML5 Media},
author = {Njål Borch and Ingar Mæhlum Arntzen},
url = {https://norceresearch.brage.unit.no/norceresearch-xmlui/bitstream/handle/11250/2711974/Norut_Tromso_rapport_28-2015.pdf?sequence=2&isAllowed=y},
isbn = {978-82-7492-319-5},
year = {2015},
date = {2015-12-08},
journal = {Norut},
abstract = {In this report we provide an extensive analysis of timing aspects of HTML5 Media, across a variety of browsers,
operating systems and media formats. Particularly we investigate how playback compares to the progression of
the local clock and how players respond to time-shifting and adjustments in playback-rate.
Additionally, we use the MediaSync JS library to enforce correctly timed playback for HTML5 media, and indicate
the effects this has on user experience. MediaSync is developed based on results from the above analysis.
MediaSync aims to provide a best effort solution that works across a variety of media formats, operating systems
and browser types, and does not make optimizations for specific permutations..
},
note = {Pre SFI},
keywords = {HTML5, MediaSync, WP4: Media Content Interaction and Accessibility},
pubstate = {published},
tppubtype = {article}
}
In this report we provide an extensive analysis of timing aspects of HTML5 Media, across a variety of browsers,
operating systems and media formats. Particularly we investigate how playback compares to the progression of
the local clock and how players respond to time-shifting and adjustments in playback-rate.
Additionally, we use the MediaSync JS library to enforce correctly timed playback for HTML5 media, and indicate
the effects this has on user experience. MediaSync is developed based on results from the above analysis.
MediaSync aims to provide a best effort solution that works across a variety of media formats, operating systems
and browser types, and does not make optimizations for specific permutations..
|
| Active learning in recommender systems Book Chapter Neil Rubens; Mehdi Elahi; Masashi Sugiyama; Dain Kaplan In: Ricci, Francesco; Rokach, Lior; Shapira, Bracha (Ed.): pp. 809-846, Springer, 2015, ISBN: 978-1-4899-7637-6, (Pre SFI). @inbook{Rubens2015,
title = {Active learning in recommender systems},
author = {Neil Rubens and Mehdi Elahi and Masashi Sugiyama and Dain Kaplan},
editor = {Francesco Ricci and Lior Rokach and Bracha Shapira},
url = {https://link.springer.com/chapter/10.1007/978-1-4899-7637-6_24},
doi = {10.1007/978-1-4899-7637-6_24},
isbn = {978-1-4899-7637-6},
year = {2015},
date = {2015-01-01},
pages = {809-846},
publisher = {Springer},
abstract = {In Recommender Systems (RS), a user’s preferences are expressed in terms of rated items, where incorporating each rating may improve the RS’s predictive accuracy. In addition to a user rating items at-will (a passive process), RSs may also actively elicit the user to rate items, a process known as Active Learning (AL). However, the number of interactions between the RS and the user is still limited. One aim of AL is therefore the selection of items whose ratings are likely to provide the most information about the user’s preferences. In this chapter, we provide an overview of AL within RSs, discuss general objectives and considerations, and then summarize a variety of methods commonly employed. AL methods are categorized based on our interpretation of their primary motivation/goal, and then sub-classified into two commonly classified types, instance-based and model-based, for easier comprehension. We conclude the chapter by outlining ways in which AL methods could be evaluated, and provide a brief summary of methods performance.},
note = {Pre SFI},
keywords = {Recommender system, WP2: User Modeling Personalization and Engagement},
pubstate = {published},
tppubtype = {inbook}
}
In Recommender Systems (RS), a user’s preferences are expressed in terms of rated items, where incorporating each rating may improve the RS’s predictive accuracy. In addition to a user rating items at-will (a passive process), RSs may also actively elicit the user to rate items, a process known as Active Learning (AL). However, the number of interactions between the RS and the user is still limited. One aim of AL is therefore the selection of items whose ratings are likely to provide the most information about the user’s preferences. In this chapter, we provide an overview of AL within RSs, discuss general objectives and considerations, and then summarize a variety of methods commonly employed. AL methods are categorized based on our interpretation of their primary motivation/goal, and then sub-classified into two commonly classified types, instance-based and model-based, for easier comprehension. We conclude the chapter by outlining ways in which AL methods could be evaluated, and provide a brief summary of methods performance. |
2014
|
| Checking, sharing, clicking and linking: Changing patterns of news use between 2004 and 2014. Journal Article Irene Costera Meijer; Tim Groot Kormelink In: Digital Journalism, vol. 3, no. 5, pp. 664-679, 2014, ISSN: 2167-0811, (Pre SFI). @article{Meijer2014,
title = {Checking, sharing, clicking and linking: Changing patterns of news use between 2004 and 2014.},
author = {Irene Costera Meijer and Tim Groot Kormelink},
url = {https://www.tandfonline.com/doi/pdf/10.1080/21670811.2014.937149?needAccess=true},
doi = {10.1080/21670811.2014.937149},
issn = { 2167-0811},
year = {2014},
date = {2014-08-01},
journal = {Digital Journalism},
volume = {3},
number = {5},
pages = {664-679},
abstract = {This paper challenges the generally taken-for-granted automatic link between media platforms, media technology and news user practices. It explores what has changed in people’s news consumption by comparing patterns in news use between 2004–2005 and 2011–2014. While new, social and mobile media technologies did not unleash a revolution in people’s dealings with news, they have facilitated, deepened and broadened user practices we already found in 2004–2005: monitoring, checking, snacking, scanning, watching, viewing, reading, listening, searching and clicking. In addition, these forms of news usage appear to increasingly order, control, organize and anchor other practices and the experience of time and environment in which they occur. Meanwhile, new and mobile news practices like linking, sharing, liking, recommending, commenting and voting have not become as central to news consumption as often assumed.},
note = {Pre SFI},
keywords = {Audience Studies, Comparative Qualitative Research, Creative Mixed Methodology, Digitalization, News Consumption, WP1: Understanding Media Experiences},
pubstate = {published},
tppubtype = {article}
}
This paper challenges the generally taken-for-granted automatic link between media platforms, media technology and news user practices. It explores what has changed in people’s news consumption by comparing patterns in news use between 2004–2005 and 2011–2014. While new, social and mobile media technologies did not unleash a revolution in people’s dealings with news, they have facilitated, deepened and broadened user practices we already found in 2004–2005: monitoring, checking, snacking, scanning, watching, viewing, reading, listening, searching and clicking. In addition, these forms of news usage appear to increasingly order, control, organize and anchor other practices and the experience of time and environment in which they occur. Meanwhile, new and mobile news practices like linking, sharing, liking, recommending, commenting and voting have not become as central to news consumption as often assumed. |
2013
|
| Method for processing a signal using an approximate map algorithm and corresponding uses Patent Alexandre Rouxel 2013, (Pre SFI). @patent{Rouxel2013,
title = {Method for processing a signal using an approximate map algorithm and corresponding uses},
author = {Alexandre Rouxel},
url = {https://patentimages.storage.googleapis.com/4f/c7/89/278cb7c94da4fd/US7512868.pdf},
year = {2013},
date = {2013-03-31},
abstract = {The invention concerns a method for processing a signal using an approximate MAP (maximum a posteriori) algorithm for determining a likelihood ratio Λk X of a set of states X of a lattice at a time k, with each of said states being associated at least one intermediate variable belonging to a group comprising a so-called forward variable and a so-called backward variable, propagated by said MAP algorithm and recursively calculated respectively in a direct orientation and in an indirect orientation at said time k relative to said lattice. The invention is characterized in that said process comprises a step which consists in reducing the number of selected states by said MAP algorithm so as to calculate said likelihood ratio, and, for at least some unselected states, in assigning to said forward variable and/or said backward variable at least one specific value, to calculate an approximate likelihood ratio.},
note = {Pre SFI},
keywords = {Map algorithm},
pubstate = {published},
tppubtype = {patent}
}
The invention concerns a method for processing a signal using an approximate MAP (maximum a posteriori) algorithm for determining a likelihood ratio Λk X of a set of states X of a lattice at a time k, with each of said states being associated at least one intermediate variable belonging to a group comprising a so-called forward variable and a so-called backward variable, propagated by said MAP algorithm and recursively calculated respectively in a direct orientation and in an indirect orientation at said time k relative to said lattice. The invention is characterized in that said process comprises a step which consists in reducing the number of selected states by said MAP algorithm so as to calculate said likelihood ratio, and, for at least some unselected states, in assigning to said forward variable and/or said backward variable at least one specific value, to calculate an approximate likelihood ratio. |
2012
|
| Representing and resolving negation for sentiment analysis Proceeding E Lapponi; J Read; Lilja Øvrelid 2012, (Pre SFI). @proceedings{Lapponi2012,
title = {Representing and resolving negation for sentiment analysis},
author = {E Lapponi and J Read and Lilja Øvrelid},
url = {https://ieeexplore.ieee.org/document/6406506},
year = {2012},
date = {2012-12-10},
note = {Pre SFI},
keywords = {WP5: Norwegian Language Technologies},
pubstate = {published},
tppubtype = {proceedings}
}
|
| Method for processing a signal using an approximate map algorithm Patent Alexandre Rouxel 2012, (Pre SFI). @patent{Rouxel2012,
title = {Method for processing a signal using an approximate map algorithm},
author = {Alexandre Rouxel},
url = {https://patentimages.storage.googleapis.com/7f/24/bf/b18b52fd129a5a/US8223820.pdf},
year = {2012},
date = {2012-07-17},
abstract = {A technique for receiving a data stream including a spreading sequence packet of information containing a data payload and, in addition to the data payload, packet overhead including at least periodic information and at least one unique section of known coded information that defines a unique position within the packet, includes performing a plurality of processing steps to detect the position of the unique section within the packet of information. The steps include detecting the periodicity of the periodic information in a first processing step; in a second processing step after periodicity in the received data stream has been determined, estimating the position of the unique section within the packet of information; and in a third processing step, correlating the information in the packet of information about the estimated position with the known coded information.},
note = {Pre SFI},
keywords = {Algorithm},
pubstate = {published},
tppubtype = {patent}
}
A technique for receiving a data stream including a spreading sequence packet of information containing a data payload and, in addition to the data payload, packet overhead including at least periodic information and at least one unique section of known coded information that defines a unique position within the packet, includes performing a plurality of processing steps to detect the position of the unique section within the packet of information. The steps include detecting the periodicity of the periodic information in a first processing step; in a second processing step after periodicity in the received data stream has been determined, estimating the position of the unique section within the packet of information; and in a third processing step, correlating the information in the packet of information about the estimated position with the known coded information. |
| Speculation and negation: Rules, rankers, and the role of syntax Journal Article Erik Velldal; Lilja Øvrelid; J Read; S Oepen In: 2012, (Pre SFI). @article{Velldal2012,
title = {Speculation and negation: Rules, rankers, and the role of syntax},
author = {Erik Velldal and Lilja Øvrelid and J Read and S Oepen},
url = {https://www.mitpressjournals.org/doi/pdf/10.1162/COLI_a_00126},
year = {2012},
date = {2012-01-01},
note = {Pre SFI},
keywords = {WP5: Norwegian Language Technologies},
pubstate = {published},
tppubtype = {article}
}
|
2003
|
| Pilot-aided channel estimation for OFDM/OQAM Conference Jean-Philippe Javaudin; D. Lacroix; Alexandre Rouxel vol. 3, The 57th IEEE Semiannual Vehicular Technology Conference 2003, (Pre SFI). @conference{Javaudin2003,
title = {Pilot-aided channel estimation for OFDM/OQAM},
author = {Jean-Philippe Javaudin and D. Lacroix and Alexandre Rouxel},
url = {https://www.researchgate.net/publication/4019779_Pilot-aided_channel_estimation_for_OFDMOQAM},
doi = {10.1109/VETECS.2003.1207088},
year = {2003},
date = {2003-05-01},
volume = {3},
pages = {1581-1585},
organization = {The 57th IEEE Semiannual Vehicular Technology Conference},
abstract = {OFDM/offsetQAM is an interesting alternative to classical OFDM modulation, as it does not require the use of guard interval. This characteristic makes its spectral efficiency optimal. On the other hand, this modulation is less robust to Rayleigh fading channel. Indeed, when classical channel estimation used for OFDM modulation is applied straightforwardly to OFDM/OQAM modulation, an intrinsic inter-symbol-interference is observed. This deeply degrades its performances. In this paper, we theoretically explain this phenomenon and propose a reliable method to significantly reduce it. Results of different methods of pilot-aided channel estimation over delay-Doppler channels are shown in this paper.},
note = {Pre SFI},
keywords = {OFDM},
pubstate = {published},
tppubtype = {conference}
}
OFDM/offsetQAM is an interesting alternative to classical OFDM modulation, as it does not require the use of guard interval. This characteristic makes its spectral efficiency optimal. On the other hand, this modulation is less robust to Rayleigh fading channel. Indeed, when classical channel estimation used for OFDM modulation is applied straightforwardly to OFDM/OQAM modulation, an intrinsic inter-symbol-interference is observed. This deeply degrades its performances. In this paper, we theoretically explain this phenomenon and propose a reliable method to significantly reduce it. Results of different methods of pilot-aided channel estimation over delay-Doppler channels are shown in this paper. |
2000
|
| Unsupervised adaptive separation of impulse signals applied to EEG analysis Conference Alexandre Rouxel; Daniel Le Guennec; Odile Macchi vol. 1, IEEE International Conference on Acoustics, Speech, and Signal Processing Turkey, 2000, (Pre SFI). @conference{Rouxel2000,
title = {Unsupervised adaptive separation of impulse signals applied to EEG analysis},
author = {Alexandre Rouxel and Daniel Le Guennec and Odile Macchi},
url = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=861997},
doi = {10.1109/ICASSP.2000.861997},
year = {2000},
date = {2000-06-05},
volume = {1},
pages = {420-423},
address = {Turkey},
organization = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
abstract = {In this paper the theoretical properties of a novel self adaptive
source separation algorithm are studied. It is a normalized
version of a modified relative gradient. It is shown that its
stability domain in terms of the normalized kurtosises of
sources is complementary of the unmodified gradient
algorithm. So it can separate a source with a very high kurtosis
from other sources having positive kurtosis. The algorithm is
then used to analyze EEG signals because they often have
positive kurtosises especially for patients suffering from
epilepsy. The good behavior of this novel algorithm is
illustrated via simulated data and then demonstrated with real
signals in an EEG analysis to separate an epileptic source from
other brain signals},
note = {Pre SFI},
keywords = {analysis},
pubstate = {published},
tppubtype = {conference}
}
In this paper the theoretical properties of a novel self adaptive
source separation algorithm are studied. It is a normalized
version of a modified relative gradient. It is shown that its
stability domain in terms of the normalized kurtosises of
sources is complementary of the unmodified gradient
algorithm. So it can separate a source with a very high kurtosis
from other sources having positive kurtosis. The algorithm is
then used to analyze EEG signals because they often have
positive kurtosises especially for patients suffering from
epilepsy. The good behavior of this novel algorithm is
illustrated via simulated data and then demonstrated with real
signals in an EEG analysis to separate an epileptic source from
other brain signals |
0000
|
MORS 2021: 1st Workshop on Multi-Objective Recommender Systems. Proceeding Abdollahpouri, Himan, Mehdi Elahi, Masoud Mansoury, Shaghayegh Sahebi, Zahra Nazari, Allison Chaney,; Babak Loni 0000. @proceedings{Abdollahpouri2021,
title = {MORS 2021: 1st Workshop on Multi-Objective Recommender Systems.},
author = {Abdollahpouri, Himan, Mehdi Elahi, Masoud Mansoury, Shaghayegh Sahebi, Zahra Nazari, Allison Chaney, and Babak Loni},
journal = {In Fifteenth ACM Conference on Recommender Systems.},
pages = {787-788},
keywords = {WP2: User Modeling Personalization and Engagement},
pubstate = {published},
tppubtype = {proceedings}
}
|
