Contextual Suggestion.
Date of Submission
December 2017
Date of Award
Winter 12-12-2018
Institute Name (Publisher)
Indian Statistical Institute
Document Type
Master's Dissertation
Degree Name
Master of Technology
Subject Name
Computer Science
Department
Computer Vision and Pattern Recognition Unit (CVPR-Kolkata)
Supervisor
Mitra, Mandar (CVPR-Kolkata; ISI)
Abstract (Summary of the Work)
In this report we give the approaches that we applied to solve TREC 2016 Contextual Suggestion Track. The goal of the Contextual Suggestion Track is to build a system capable of proposing venues which a user might be interested to visit, using any contextual and personal information. We present our approaches to model Point Of Interests(POI) and user profile based on tags’ word embedding(specifically Word2Vec). We also present model for contextual relevance and POI relevance. We also compare different ways to tune the parameters. Our approaches work better than other existing approaches presented in TREC Contextual Suggestion 2016 Track.
Control Number
ISI-DISS-2017-365
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
DOI
http://dspace.isical.ac.in:8080/jspui/handle/10263/6890
Recommended Citation
Agrawal, Suraj, "Contextual Suggestion." (2018). Master’s Dissertations. 264.
https://digitalcommons.isical.ac.in/masters-dissertations/264
Comments
ProQuest Collection ID: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:28843288