An Analysis Framework for Content-based Job Recommendation

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Title: An Analysis Framework for Content-based Job Recommendation
Authors: Guo, Xingsheng
Jerbi, Houssem
O'Mahony, Michael P.
Permanent link: http://hdl.handle.net/10197/6107
Date: 29-Sep-2014
Abstract: In this paper, we focus on the task of job recommendation. In particular, we consider several personalised content-based and case-based approaches to recommendation. We investigate a number of feature-based item representations, along with a variety of feature weighting schemes. A comparative evaluation of the various approaches is performed using a realworld, open source dataset.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Copyright (published version): 2014 the Author
Keywords: Recommender Systems;Open data
Language: en
Status of Item: Peer reviewed
Conference Details: 22nd International Conference on Case-Based Reasoning (ICCBR), Cork, Ireland, 29 September - 01 October 2014
Appears in Collections:Insight Research Collection

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