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      Word Embedding based Approaches for Information Retrieval

      Seventh BCS-IRSG Symposium on Future Directions in Information Access (FDIA)

      Future Directions in Information Access

      5 September 2017

      Word Embedding, Information Retrieval

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          Abstract

          The interest on using word embedding has expanded in various areas of text processing in recent years following the introduction of the word2vec model by Mikolov et al. (2013) and Pennington et al. (2014). The word embedding models use a large amount of text to create low dimensional representations of words capturing relationships between words without any external supervision. The resultant representation is shown to replicate many linguistic regularities such as, semantic similarity between terms, conceptual composition of terms, laws of analogy of terms. These features can be used for Information Retrieval (IR) where, the retrieval functions primarily depend on statistical co-occurrences.

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          Relevance based language models

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            Word Embedding based Generalized Language Model for Information Retrieval

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              Author and article information

              Contributors
              Conference
              September 2017
              September 2017
              : 1-4
              Affiliations
              Indian Statistical Institute, Kolkata

              203, B.T. Road

              Kolkata, India - 700108
              Article
              10.14236/ewic/FDIA2017.9
              © Roy. Published by BCS Learning and Development Ltd. Proceedings of the 7th Symposium on Future Directions in Information Access 2017

              This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

              Seventh BCS-IRSG Symposium on Future Directions in Information Access
              FDIA
              7
              Barcelona, Spain
              5 September 2017
              Electronic Workshops in Computing (eWiC)
              Future Directions in Information Access
              Product
              Product Information: 1477-9358BCS Learning & Development
              Self URI (journal page): https://ewic.bcs.org/
              Categories
              Electronic Workshops in Computing

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