Abstract
The bag of words representation (BoW), which is widely used in information retrieval (IR), represents documents and queries as word lists that do not express anything about context information. When we look for information, we find that not everything is explicitly stated in a document, so context information is needed to understand its content. This paper proposes the use of bag of concepts (BoC) and Holographic reduced representation (HRR) in IR. These representations go beyond BoW by incorporating context information to document representations. Both HRR and BoC are produced using a vector space methodology known as Random Indexing, and allow expressing additional knowledge from different sources. Our experiments have shown the feasibility of the representations and improved the mean average precision by up to 7% when they are compared with the traditional vector space model.
The first author was supported by scholarship 217251/ 208265, second author by scholarship 165545 granted by CONACYT, while the third, fifth and sixth author were partially supported by SNI, Mexico.
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Carrillo, M., Villatoro-Tello, E., López-López, A., Eliasmith, C., Montes-y-Gómez, M., Villaseñor-Pineda, L. (2009). Representing Context Information for Document Retrieval. In: Andreasen, T., Yager, R.R., Bulskov, H., Christiansen, H., Larsen, H.L. (eds) Flexible Query Answering Systems. FQAS 2009. Lecture Notes in Computer Science(), vol 5822. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04957-6_21
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DOI: https://doi.org/10.1007/978-3-642-04957-6_21
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