@conference{Tessem2019b,

title = {Analogical News Angles from Text Similarity},

author = {Bjørnar Tessem},

editor = {Max Bramer and Miltos Petridis},

url = {https://bora.uib.no/bora-xmlui/bitstream/handle/1956/22473/SGAI_2019.pdf?sequence=4&isAllowed=y},

doi = {https://doi.org/10.1007/978-3-030-34885-4_35},

year  = {2019},

date = {2019-11-19},

booktitle = {Artificial Intelligence XXXVI},

number = {11927},

pages = {449–455},

publisher = {Springer International Publishing},

abstract = {The paper presents an algorithm providing creativity support to journalists. It suggests analogical transfer of news angles from reports written about different events than the one the journalist is working on. The problem is formulated as a matching problem, where news reports with similar wordings from two events are matched, and unmatched reports from previous cases are selected as candidates for a news angle transfer. The approach is based on document similarity measures for matching and selection of transferable candidates. The algorithm has been tested on a small data set and show that the concept may be viable, but needs more exploration and evaluation in journalistic practice.},

note = {Pre SFI},

keywords = {Analogical reasoning, Computational creativity, Document similarity, Journalism, WP3: Media Content Production and Analysis},

pubstate = {published},

tppubtype = {conference}

}