Ecole d'ingénieur et centre de recherche en Sciences du numérique

The concentric nature of news semantic Snapshots: Knowledge extraction for semantic annotation of news items

Redondo Garcia, José Luis; Rizzo, Giuseppe; Troncy, Raphaël

K-CAP 2015, 8th International Conference on Knowledge Capture, October 7-10, 2015, Palisades, NY, USA

Best Paper Award

The Web enables to have access to silo-ed information describing news articles, often offering a multitude of viewpoints that, once combined, can provide a broader picture of the story being reported on the news. In this paper, we propose an approach that automatically extracts representative features of a news item, namely named entities, from textual content attached to a video item (subtitles) and from a set of documents from the Web collected using entity expansion techniques. Approaches relying on entity expansion generally try to collect and process the important facts behinds a particular news item, but they are often too dependent on frequency-based functions and information retrieval techniques thus neglecting the multi-dimensional relationships that are established among the entities. We propose a concentric-based approach that enables to represent the context of a news item, by harmonizing into a single model the representative entities, which can be extracted using information retrieval and natural language processing techniques (Core), and other entities that get prominent according to different dimensions such as informativeness, semantic connectivity, or popularity (Crust). We compare our approach with a baseline by analyzing the compactness of the generated summary on an existing gold standard available on the Web. Results of the experiments show that our approach converges faster to the ideal compact news snapshot with an improvement of 30.1% over the baseline. 

Document Doi Bibtex

Titre:The concentric nature of news semantic Snapshots: Knowledge extraction for semantic annotation of news items
Mots Clés:Semantic Annotation, Entity Expansion, News Item
Type:Conférence
Langue:English
Ville:Palisades
Pays:ÉTATS-UNIS
Date:
Département:Data Science
Eurecom ref:4680
Copyright: © ACM, 2015. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in K-CAP 2015, 8th International Conference on Knowledge Capture, October 7-10, 2015, Palisades, NY, USA http://dx.doi.org/10.1145/2815833.2815836
Bibtex: @inproceedings{EURECOM+4680, doi = {http://dx.doi.org/10.1145/2815833.2815836}, year = {2015}, title = {{T}he concentric nature of news semantic {S}napshots: {K}nowledge extraction for semantic annotation of news items}, author = {{R}edondo {G}arcia, {J}os{\'e} {L}uis and {R}izzo, {G}iuseppe and {T}roncy, {R}apha{\"e}l}, booktitle = {{K}-{CAP} 2015, 8th {I}nternational {C}onference on {K}nowledge {C}apture, {O}ctober 7-10, 2015, {P}alisades, {NY}, {USA}}, address = {{P}alisades, {\'{E}}{TATS}-{UNIS}}, month = {10}, url = {http://www.eurecom.fr/publication/4680} }
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