About Me

I am a post-doctoral researcher in the School of Informatics at the University of Edinburgh. My current focus is on understanding clusters of long term conditions (multimorbidity) in patients using machine learning. I also worked on an EU Horizon 2020 funded research project Helios exploring ways of learning users' activities, and contexts for making personalized connections, and content sharing over (decentralized) social networks.

I graduated with a PhD in Computer Science from Trinity College Dublin in March 2021. My PhD supervisor was the late Prof. Séamus (Shay) Lawless, and later I was supervised by Prof. Owen Conlan. My PhD thesis, broadly speaking, is about exploring Information Retrieval based approaches for contextual recommendation, with a particular focus to improve precision at top ranks.

Check out our recent Inf. Retr. J. and SIGIR 2020 work on how to effectively recommend 'points of interests' to users catering to their personalized preferences, and CIKM 2020 work on relevance feedback with query variants.

Research Interests

  • Information Retrieval
  • Contextual Recommendation
  • Machine Learning
  • Generally speaking, my research interests include personalised information retrieval, contextual recommendation, and information retrieval from noisy texts. More specific keywords are Search; Retrieval models; Relevance feedback; Word/context embedding; User preference modeling; Simulated user agents; Unsupervised, weakly supervised, and supervised (learning to rank) approaches applied in different retrieval and recommendation tasks.

    Books, etc.

  • Introduction to Information Retrieval Manning, Raghavan and Schutze, Cambridge University Press, 2008.
  • Search Engines Information Retrieval in Practice W. Bruce Croft, D. Metzler, T. Strohman, Pearson, 2009.
  • Recommender Systems Handbook Francesco Ricci, Lior Rokach, Bracha Shapira, Paul B. Kantor, Springer, 2010.

  • Teaching

  • Co-supervisor, Trinity College Dublin (2018 - 19), Master's thesis: Twitter as an Alternative Review Site.
  • Lab, Information Retrieval and Web Search, Trinity College Dublin (2017 - 18, 2018 - 19).
  • Lab, Algorithms & Data Structures (using C/Java), Trinity College Dublin (Jan '17 - Mar '17, Oct '17 - Dec '17, Jan '18 - Mar '18, Sep '18 - Nov '18, Sep '19 - Nov '19).
  • Lab, Computer Engineering 1 (C++), Trinity College Dublin (Mar '18 - Apr '18, Jan '19 - Apr '19, Jan '20 - Apr '20).
  • Lab, Programming Project with Processing at Trinity College Dublin (Jan '17 - Mar '17, Feb '18).

  • Academic Activities

  • Reviewer, ACM SIGIR, ACM TALLIP, ACM IKDD CODS-COMAD, Springer SNCS, ACM Hypertext 2018, WEPIR@ACM CHIIR, FIRE 2014.
  • Organizing/Program Committee member, Forum for Information Retrieval Evaluation (FIRE) since 2012.
  • Publications

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  • Anirban Chakraborty, Debasis Ganguly, Annalina Caputo, and Gareth J. F. Jones. Kernel Density Estimation based Factored Relevance Model for Multi-Contextual Point-of-Interest Recommendation. Inf. Retr. J. Springer. [link][Preprint]

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  • Anirban Chakraborty, Debasis Ganguly, and Owen Conlan. Retrievability based Document Selection for Relevance Feedback with Automatically Generated Query Variants. ACM CIKM 2020. [link][PDF][video presentation]

  • Anirban Chakraborty, Debasis Ganguly, and Owen Conlan. Relevance Models for Multi-Contextual Appropriateness in Point-of-Interest Recommendation. ACM SIGIR 2020. [link][PDF][video presentation]

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  • Anirban Chakraborty, Debasis Ganguly, Annalina Caputo, and Séamus Lawless. A Factored Relevance Model for Contextual Point-of-Interest Recommendation. ACM SIGIR ICTIR 2019. [link][PDF]

  • Mostafa Bayomi, Annalina Caputo, Matthew Nicholson, Anirban Chakraborty, and Séamus Lawless. CoRE: a cold-start resistant and extensible recommender system. ACM SAC 2019. [link]

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  • Anirban Chakraborty. Enhanced Contextual Recommendation using Social Media Data. ACM SIGIR 2018. [link][PDF]

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  • Anirban Chakraborty. Exploring Search Behaviour in Microblogs. FDIA 2017. [link][PDF]

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  • Kripabandhu Ghosh, Anirban Chakraborty, Swapan Kumar Parui and Prasenjit Majumder. Improving Information Retrieval Performance on OCRed Text in the Absence of Clean Text Ground Truth. Inf. Process. Manag. 52 (5), 873 - 884. Elsevier. [link][PDF]

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  • Anirban Chakraborty, Kripabandhu Ghosh and Swapan Kumar Parui. Retrieval from Noisy E-Discovery Corpus in the Absence of Training Data. ACM SIGIR 2015. [link][PDF]

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  • Anirban Chakraborty, Kripabandhu Ghosh and Swapan Kumar Parui. Building Test Collection from Old IR Literature. In FIRE 2014 proceedings. ACM DL. [link][PDF]

  • Anirban Chakraborty, Kripabandhu Ghosh and Utpal Roy. A Word Association Based Approach for Improving Retrieval Performance from Noisy OCRed Text. KDIR 2014. SCITEPRESS. [link][PDF]

  • S. Baral, S. Bhattacharya, A. Chakraborty, U. Bhattacharya and S. K. Parui. A Machine Learning Approach to Detection of Core Region of Online Handwritten Bangla Word Samples. ICFHR 2014. IEEE. [link]

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  • Kripabandhu Ghosh, Anirban Chakraborty and Swapan Kumar Parui. Improving IR performance from OCRed text using cooccurrence. In FIRE 2013 proceedings. ACM DL. [link][PDF]

  • Find me on Google Scholar, DBLP


    School of Informatics,
    10 Crichton Street,
    Edinburgh, EH8 9AB.


    Knowledge and Data Engineering Group