The vocabulary problem in human-system communication
Communications of the ACM
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Modern Information Retrieval
The Journal of Machine Learning Research
PageRank without hyperlinks: structural re-ranking using links induced by language models
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Improving web search results using affinity graph
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Regularizing ad hoc retrieval scores
Proceedings of the 14th ACM international conference on Information and knowledge management
Respect my authority!: HITS without hyperlinks, utilizing cluster-based language models
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
LDA-based document models for ad-hoc retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Information Retrieval
Introduction to Information Retrieval
Effective latent space graph-based re-ranking model with global consistency
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Explicit versus latent concept models for cross-language information retrieval
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
A Wikipedia-based multilingual retrieval model
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
CLEF 2009 ad hoc track overview: TEL and Persian tasks
CLEF'09 Proceedings of the 10th cross-language evaluation forum conference on Multilingual information access evaluation: text retrieval experiments
Evaluating cross-language explicit semantic analysis and cross querying
CLEF'09 Proceedings of the 10th cross-language evaluation forum conference on Multilingual information access evaluation: text retrieval experiments
Ontology-driven extraction of linguistic patterns for modelling clinical guidelines
AIME'05 Proceedings of the 10th conference on Artificial Intelligence in Medicine
A late fusion approach to cross-lingual document re-ranking
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
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The field of information retrieval still strives to develop models which allow semantic information to be integrated in the ranking process to improve performance in comparison to standard bag-of-words based models. A conceptual model has been adopted in general-purpose retrieval which can comprise a range of concepts, including linguistic terms, latent concepts and explicit knowledge concepts. One of the drawbacks of this model is that the computational cost is significant and often intractable in modern test collections. Therefore, approaches utilising concept-based models for re-ranking initial retrieval results have attracted a considerable amount of study. This method enjoys the benefits of reduced document corpora for semantic space construction and improved ranking results. However, fitting such a model to a smaller collection is less meaningful than fitting it into the whole corpus. This paper proposes a dual-space model which incorporates external knowledge to enhance the space produced by the latent concept method. This model is intended to produce global consistency across the semantic space: similar entries are likely to have the same re-ranking scores with respect to the latent and manifest concepts. To illustrate the effectiveness of the proposed method, experiments were conducted using test collections across different languages. The results demonstrate that the method can comfortably achieve improvements in retrieval performance.