Name
Abstract | ||
|---|---|---|
Opinion mining has become recently a major research topic. A wide range of techniques have been proposed to enable opinion-oriented information seeking systems. However, little is known about the ability of opinion-related information to improve regular retrieval tasks. Our hypothesis is that standard retrieval methods might benefit from the inclusion of opinion-based features. A sentence retrieval scenario is a natural choice to evaluate this claim. We propose here a formal method to incorporate some opinion-based features of the sentences as query-independent evidence. We show that this incorporation leads to retrieval methods whose performance is significantly better than the the performance of state of the art sentence retrieval models. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1645953.1646186 | CIKM |
Keywords | Field | DocType |
formal method,opinion-based feature,major research topic,opinion-related information,opinion-oriented information,art sentence retrieval model,regular retrieval task,retrieval method,standard retrieval method,sentence retrieval scenario,opinion mining | Data mining,Cognitive models of information retrieval,Computer science,Natural language processing,Artificial intelligence,Formal methods,Term Discrimination,Human–computer information retrieval,Information retrieval,Information seeking,Sentiment analysis,Relevance (information retrieval),Sentence | Conference |
Citations | PageRank | References |
4 | 0.42 | 9 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ronald T. Fernández | 1 | 33 | 3.78 |
| David E. Losada | 2 | 326 | 40.63 |