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        <title>Text Retrieval by Term Co-occurrences in a Query-based Vector Space</title>
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            <title>Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers</title>
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            <namePart type="given">Yuji</namePart>
            <namePart type="family">Matsumoto</namePart>
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            <namePart type="given">Rashmi</namePart>
            <namePart type="family">Prasad</namePart>
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    <abstract>Term co-occurrence in a sentence or paragraph is a powerful and often overlooked feature for text matching in document retrieval. In our experiments with matching email-style query messages to webpages, such term co-occurrence helped greatly to filter and rank documents, compared to matching document-size bags-of-words. The paper presents the results of the experiments as well as a text-matching model where the query shapes the vector space, a document is modelled by two or three vectors in this vector space, and the query-document similarity score depends on the length of the vectors and the relationships between them.</abstract>
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%0 Conference Proceedings
%T Text Retrieval by Term Co-occurrences in a Query-based Vector Space
%A Sneiders, Eriks
%Y Matsumoto, Yuji
%Y Prasad, Rashmi
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F sneiders-2016-text
%X Term co-occurrence in a sentence or paragraph is a powerful and often overlooked feature for text matching in document retrieval. In our experiments with matching email-style query messages to webpages, such term co-occurrence helped greatly to filter and rank documents, compared to matching document-size bags-of-words. The paper presents the results of the experiments as well as a text-matching model where the query shapes the vector space, a document is modelled by two or three vectors in this vector space, and the query-document similarity score depends on the length of the vectors and the relationships between them.
%U https://aclanthology.org/C16-1222
%P 2356-2365

Markdown (Informal)

[Text Retrieval by Term Co-occurrences in a Query-based Vector Space](https://aclanthology.org/C16-1222) (Sneiders, COLING 2016)

• Text Retrieval by Term Co-occurrences in a Query-based Vector Space (Sneiders, COLING 2016)

ACL

• Eriks Sneiders. 2016. Text Retrieval by Term Co-occurrences in a Query-based Vector Space. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 2356–2365, Osaka, Japan. The COLING 2016 Organizing Committee.