Avishek Anand

Post-Doc Researcher @ L3S research center

Avishek Anand

Post-doc Researcher @ L3S Research Center

Current Affiliation: L3S Research Center.
Leibniz University, Hannover
Address: L3S Research Center, Appelstra├če 9a, Hannover.
Phone: +49 0511 762 17795
Fax: +49 0511 762 17779
Email: anand (at) l3s . de

[Linkedin] [L3S Home] [Google Scholar]

Research Interests



My research focusses on retrieval, mining, analysis and data management aspects of temporal Web collections like Web archives, Wikipedia and news collections. You can find my publications here . I am broadly interested in :

  • Indexing Methods for Text.

  • Wikipedia Enrichment using text mining and retrieval techniques.

  • Retrieval models for temporal collections.

  • Large scale study and evolutionary analysis of Web archives.

  • Graph data management.



  • Projects




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    Wikipedia Enrichment

    Wikipedia entity pages are a valuable source of information for direct consumption and for knowledge-base construction, update and maintenance. Facts in these entity pages are typically supported by references. Our studies show that as much as 20% of the references are from online news sources. However, many entity pages are incomplete even if relevant information is already available in existing news articles. Even for the already present references, there is often a delay between the news article publication time and the reference time. In this work, we look at Wikipedia through the lens of news and investigate approaches to enrich Wikipedia with potentially missing facts, citations, etc.

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    HistDiv - Historical Search

    Longitudinal corpora like newspaper archives are of immense value to historical research, and time as an important factor for historians strongly influences their search behaviour in these archives. While searching for articles published over time, a key preference is to retrieve documents which cover the important aspects from important points in time which is different from standard search behavior. We are developing HistDiv which is a search and exploration system for searching historical news collections.

    Go to Histdiv

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    Tempas - Tag-based Archive Exploration

    Tempas is a search engine incorporating social tags in order to enable richer search capabilities on archived Web sites than currently available. Tempas is based on tags posted on Delicious, which describe a website at a very specific time. This temporal information allows to search an archive for the desired version of a website in a given time period and is percieved as an improvement over accessing an archive by providing the exact URL and time of a website's version, like most Web archives only allow today.

    Go to Tempas

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    Temporal Indexing and Query Processing

    For realizing efficient access to longitudinal collections, keyword queries are extended by temporal predicates giving temporal queries of the form -- "alexandria @ [2008-2011]". This line of work explores indexing and query processing methods for efficient temporal querying, index maintenance and approximate query processing.



    Brief CV



    2014-now Post-doctoral Researcher
    L3S Research Center, Hannover.
    2009-2013 Phd Student.
    Department of Databases and Information Systems, Max Planck Institute for Informatics, Saarbruecken.
    2007-2009 Masters Student.
    Saarland University and Max Planck Institute for Informatics, Saarbruecken.
    2005-2007 Software Engineer.
    Microsoft, India Development Center.
    2001-2005 Bachelor Student.
    Indian Institute of Information Technology, Allahabad.