Grčar et al., 2005
ViewPDF| Publication | Publication Date | Title |
|---|---|---|
| Grčar et al. | User profiling for interest-focused browsing history | |
| Batsakis et al. | Improving the performance of focused web crawlers | |
| Bedi et al. | Focused crawling of tagged web resources using ontology | |
| Kennedy et al. | Query-adaptive fusion for multimodal search | |
| Sieg et al. | Representing context in web search with ontological user profiles | |
| Wang et al. | Using evidence based content trust model for spam detection | |
| Dong et al. | State of the art in semantic focused crawlers | |
| Han et al. | Folksonomy-based ontological user interest profile modeling and its application in personalized search | |
| Kubatz et al. | LocalRank-Neighborhood-based, fast computation of tag recommendations | |
| Hsu et al. | Efficient and effective prediction of social tags to enhance web search | |
| Preetha et al. | Personalized search engines on mining user preferences using clickthrough data | |
| Ahamed et al. | Deduce user search progression with feedback session | |
| Jayarathna et al. | Unified relevance feedback for multi-application user interest modeling | |
| Garg | Automatic text summarization of video lectures using subtitles | |
| Bhowmick et al. | Ontology Based User Modeling for Personalized Information Access. | |
| Chakraborti et al. | Product news summarization for competitor intelligence using topic identification and artificial bee colony optimization | |
| Shirgave et al. | Semantically enriched web usage mining for predicting user future movements | |
| Krishnan et al. | Select, link and rank: Diversified query expansion and entity ranking using wikipedia | |
| Roy | Predicting User’s web navigation behaviour using AMD and HMM approaches | |
| Alper et al. | Personalized recommendation in folksonomies using a joint probabilistic model of users, resources and tags | |
| Song | Exploring concept graphs for biomedical literature mining | |
| Nakatani et al. | Quality evaluation of search results by typicality and speciality of terms extracted from wikipedia | |
| Gugnani et al. | A complete survey on web document ranking | |
| Hussein et al. | A user-concept matrix clustering algorithm for efficient next page prediction | |
| Wang et al. | Content trust model for detecting web spam |