Memory Based Collaborative Filtering with Lucene

• URL: http://arxiv.org/abs/1607.00223v2
• Date: Mon, 18 Nov 2024 07:36:40 GMT
• Title: Memory Based Collaborative Filtering with Lucene
• Authors: Claudio Gennaro,
• Abstract summary: Memory Based Collaborative Filtering is a widely used approach to provide recommendations. A disadvantage of this approach is the loss of generality and flexibility of the general collaborative filtering systems. We have developed a methodology that allows one to build a scalable and effective collaborative filtering system on top of a conventional full-text search engine.
• Score: 2.7170928704980253
• License:
• Abstract: Memory Based Collaborative Filtering is a widely used approach to provide recommendations. It exploits similarities between ratings across a population of users by forming a weighted vote to predict unobserved ratings. Bespoke solutions are frequently adopted to deal with the problem of high quality recommendations on large data sets. A disadvantage of this approach, however, is the loss of generality and flexibility of the general collaborative filtering systems. In this paper, we have developed a methodology that allows one to build a scalable and effective collaborative filtering system on top of a conventional full-text search engine such as Apache Lucene.

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