Memory Based Collaborative Filtering with Lucene
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arXiv
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| Format: | Preprint |
| Published: |
2016
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| _version_ | 1866913579302649856 |
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| author | Gennaro, Claudio |
| author_facet | Gennaro, Claudio |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_1607_00223 |
| institution | arXiv |
| publishDate | 2016 |
| record_format | arxiv |
| spellingShingle | Memory Based Collaborative Filtering with Lucene Gennaro, Claudio Information Retrieval H.3.3; H.3.1 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. |
| title | Memory Based Collaborative Filtering with Lucene |
| topic | Information Retrieval H.3.3; H.3.1 |
| url | https://arxiv.org/abs/1607.00223 |