So far, most of the publicly available Page/Image/Video search engines (e.g., Google, Yahoo, MSN) adopts query-list paradigm, that is, when a user submits a query, the search engine returns a ranking list of pages/images/videos. The higher on the list, the more relevant to the query the page/image/video is supposed to be. This approach works efficiently for well-defined narrow queries, when the query is too general or even ambiguous, e.g., “jaguar”, “apple”, the users may have to sift through the list to locate the interest. For example, for query “apple”, pages/images/videos of apple fruit are intermixed with pages/images/videos of apple ipod, apple logo, apple pie, and so on
Latent Semantic Analysis (LSA) is widely used for finding the documents whose semantic is similar to...
Latent semantic indexing (LSI) can be used in patent searching to overcome drawbacks of Boolean sear...
AbstractLatent semantic indexing (LSI) is an information retrieval technique based on the spectral a...
Documents retrieved in response to a user’s query should reflect the intention of the user. Keyword ...
Latent Semantic Indexing (LSI) promises more accurate retrieval of information by incorporating stat...
Abstract — LSI is a powerful, generic practice which is able to index any document collection. It ca...
Latent Semantic Indexing (LSI) is commonly used to match queries to documents in information retriev...
We have previously described an extension of the vector retrieval method called "Latent Semanti...
When people search for documents, they eventually want content, not words. Hence, search engines sho...
[[abstract]]Latent Semantic Indexing (LSI) is a retrieval technique that employs Singular Value Deco...
In this paper we present a theoretical model for understanding the performance of Latent Semantic In...
Latent semantic indexing (LSI) is an information retrieval technique based on the spectral analysis ...
We investigate the effect of using customized profiles to help searching relevant servers in Interne...
In this article we propose Supervised Semantic Indexing (SSI) an algorithm that is trained on (query...
We incorporate the Latent Semantic Indexing (LSl) technique into a competition-based neural network ...
Latent Semantic Analysis (LSA) is widely used for finding the documents whose semantic is similar to...
Latent semantic indexing (LSI) can be used in patent searching to overcome drawbacks of Boolean sear...
AbstractLatent semantic indexing (LSI) is an information retrieval technique based on the spectral a...
Documents retrieved in response to a user’s query should reflect the intention of the user. Keyword ...
Latent Semantic Indexing (LSI) promises more accurate retrieval of information by incorporating stat...
Abstract — LSI is a powerful, generic practice which is able to index any document collection. It ca...
Latent Semantic Indexing (LSI) is commonly used to match queries to documents in information retriev...
We have previously described an extension of the vector retrieval method called "Latent Semanti...
When people search for documents, they eventually want content, not words. Hence, search engines sho...
[[abstract]]Latent Semantic Indexing (LSI) is a retrieval technique that employs Singular Value Deco...
In this paper we present a theoretical model for understanding the performance of Latent Semantic In...
Latent semantic indexing (LSI) is an information retrieval technique based on the spectral analysis ...
We investigate the effect of using customized profiles to help searching relevant servers in Interne...
In this article we propose Supervised Semantic Indexing (SSI) an algorithm that is trained on (query...
We incorporate the Latent Semantic Indexing (LSl) technique into a competition-based neural network ...
Latent Semantic Analysis (LSA) is widely used for finding the documents whose semantic is similar to...
Latent semantic indexing (LSI) can be used in patent searching to overcome drawbacks of Boolean sear...
AbstractLatent semantic indexing (LSI) is an information retrieval technique based on the spectral a...