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Search Logs Mining: Survey

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Proceedings of First International Conference on Information and Communication Technology for Intelligent Systems: Volume 2

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 51))

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Abstract

Search engine process millions of query and collect data of user interaction every day. These huge amount of data contains valuable information through which web search engine can be optimized. Search engine mostly relies on explicit judgement received from domain experts. To survive the competition search engine must understand user’s information needs very well. Search logs provide implicit data about user’s interaction with search engine. Search logs are noisy, they contain data of both successful search and unsuccessful search. The challenge is to accurately interpret user’s feedback to search engine and learning the user access patterns, such that search engine will better be able to cater the user’s information needs. User feedback can be used to re-rank the search result, query suggestion and URL recommendation.

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Authors and Affiliations

  1. Government Engineering College Gandhinagar, Gandhinagar, India

    Vivek Bhojawala & Pinal Patel

Authors
  1. Vivek Bhojawala
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  2. Pinal Patel
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Corresponding author

Correspondence to Vivek Bhojawala .

Editor information

Editors and Affiliations

  1. Deparment of CSE, Anil Neerukonda Ins. of Tech. & Sci., Vishakapatnam, India

    Suresh Chandra Satapathy

  2. Indian Statistical Institute, Jadavpur University, Kolkata, India

    Swagatam Das

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© 2016 Springer International Publishing Switzerland

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Bhojawala, V., Patel, P. (2016). Search Logs Mining: Survey. In: Satapathy, S., Das, S. (eds) Proceedings of First International Conference on Information and Communication Technology for Intelligent Systems: Volume 2. Smart Innovation, Systems and Technologies, vol 51. Springer, Cham. https://doi.org/10.1007/978-3-319-30927-9_4

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  • DOI: https://doi.org/10.1007/978-3-319-30927-9_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30926-2

  • Online ISBN: 978-3-319-30927-9

  • eBook Packages: EngineeringEngineering (R0)

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