Loading...
Please wait, while we are loading the content...
Similar Documents
Topic Based Query Suggestion Using Hidden Topic Model for Effective Web Search
| Content Provider | Semantic Scholar |
|---|---|
| Author | Barathi, M. Valli, Seppo |
| Copyright Year | 2014 |
| Abstract | Keyword-based web search is widely used for locatin g information on the web. But, web users lack sufficient domain knowledge and find it difficult t o organize and formulate input queries which affect search performance. Existing method suggests terms using the statistics in the documents, query logs a nd external dictionaries. This novel query suggestion method suggests terms related to topics present in the input query and re-rank the retrieved documents. A generative model, Latent Dirichlet Allocation (LDA) is used to learn the topics from the underlying docume nts. The high probability words in a topic are sele cted using the Kullback liebler(KL) divergence measure and presented to the user for suggestion, to enrich the user query and to narrow the search. The re-rankin g technique of this approach uses the initial retri eval position of the document to re-rank the documents. The suggested queries by the hidden topic approach and by keyword search are analysed. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.jatit.org/volumes/Vol59No3/12Vol59No3.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
