Publicação
Query expansion with temporal segmented texts
| Resumo: | The use of temporal data extracted from text, to improve the effectiveness of Information Retrieval systems, has recently been the focus of important research work. Our research hypothesis is that the usage of the temporal relationship between words improves the Information Retrieval results. For this purpose, the texts are temporally segmented to establish a relationship between words and dates found in texts. This approach was applied in Query Expansion systems, using a collection with Portuguese newspaper texts. The results showed that the use of the temporality of words can enhance retrieval effectiveness. In particular for time-sensitive queries, we achieved 9.5% improvement in Precision@10. To our knowledge, this is the first work using temporal text segmentation to improve retrieval results. |
|---|---|
| Autores principais: | Craveiro, Olga |
| Outros Autores: | Macedo, Joaquim; Madeira, Henrique |
| Assunto: | Temporal information retrieval Query expansion Temporal text segmentation |
| Ano: | 2014 |
| País: | Portugal |
| Tipo de documento: | comunicação em conferência |
| Tipo de acesso: | acesso restrito |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | The use of temporal data extracted from text, to improve the effectiveness of Information Retrieval systems, has recently been the focus of important research work. Our research hypothesis is that the usage of the temporal relationship between words improves the Information Retrieval results. For this purpose, the texts are temporally segmented to establish a relationship between words and dates found in texts. This approach was applied in Query Expansion systems, using a collection with Portuguese newspaper texts. The results showed that the use of the temporality of words can enhance retrieval effectiveness. In particular for time-sensitive queries, we achieved 9.5% improvement in Precision@10. To our knowledge, this is the first work using temporal text segmentation to improve retrieval results. |
|---|