Designing topic shifts with graphs
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Redalyc
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| Format: | Artículo científico |
| Langue: | en |
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Asociación Española para la Inteligencia Artificial
2007
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| _version_ | 1876461952121700352 |
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| author | Martín I. Rezk |
| author_facet | Martín I. Rezk |
| contents | Designing topic shifts with graphs Martín I. Rezk Laura Alonso i Alemany Ingeniería Graphs in NLP document topic Document navigation We present Cheshire, a recommendation system to help in building reading lists for topic shifts. Given adocument collection, a starting topic and a target topic (expressed by keywords), Cheshire recommendsthe sequence of documents that bridges the gap between input and target topics with the smallest differencein content between each document. To do that, the document collection is represented as a graph, wheredocuments are nodes related by weighted edges. Edges are created whenever a set of words is shared bytwo documents. In this paper we present experiments with different methods for choosing words that createedges, and the weights to be assigned to each edge. Results are evaluated by comparison with a dummybaseline and with a manually created gold standard 2007 artículo científico 1137-3601 https://www.redalyc.org/articulo.oa?id=92503605 en http://www.redalyc.org/revista.oa?id=925 Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial application/pdf Asociación Española para la Inteligencia Artificial Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial (España) Num.36 Vol.11 |
| format | Artículo científico |
| id | redalyc_92503605 |
| institution | Redalyc |
| language | en |
| publishDate | 2007 |
| publisher | Asociación Española para la Inteligencia Artificial |
| spellingShingle | Designing topic shifts with graphs Martín I. Rezk Ingeniería Graphs in NLP document topic Document navigation Designing topic shifts with graphs Martín I. Rezk Laura Alonso i Alemany Ingeniería Graphs in NLP document topic Document navigation We present Cheshire, a recommendation system to help in building reading lists for topic shifts. Given adocument collection, a starting topic and a target topic (expressed by keywords), Cheshire recommendsthe sequence of documents that bridges the gap between input and target topics with the smallest differencein content between each document. To do that, the document collection is represented as a graph, wheredocuments are nodes related by weighted edges. Edges are created whenever a set of words is shared bytwo documents. In this paper we present experiments with different methods for choosing words that createedges, and the weights to be assigned to each edge. Results are evaluated by comparison with a dummybaseline and with a manually created gold standard 2007 artículo científico 1137-3601 https://www.redalyc.org/articulo.oa?id=92503605 en http://www.redalyc.org/revista.oa?id=925 Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial application/pdf Asociación Española para la Inteligencia Artificial Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial (España) Num.36 Vol.11 |
| title | Designing topic shifts with graphs |
| topic | Ingeniería Graphs in NLP document topic Document navigation |
| url | https://www.redalyc.org/articulo.oa?id=92503605 |