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Content-Based Recommendation Generator (CBRec v1.0)

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A Python library which generates content-based recommendations for a set of items described by textual metadata using four possible vector space methods, namely TF-IDF, LSI, RP and LDA.

The library can be used in command line or directly in a Python program. It takes as input a JSON file which contains an array of hashes that describe the metadata of items and generates an output JSON file which contains the same item hashes augmented with two more attributes, namely (i) rec attribute which contains the top-N recommendations for each item, represented by an array of item IDs and (ii) rec_scores attribute which contains the top-N similarity scores, represented by an array of float numbers.


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Resource Information
Resource type: software
Date: Dec 12, 2014
Size: 145 Ko
Ownership: Idiap Research Institute
Distribution: Web
Contact: Nikolaos PAPPAS
+41 277 217 814
+41 277 217 729