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Rank and relevance in novelty and diversity metrics for recommender systems
A formal framework for the definition of novelty and diversity metrics is presented that unifies and generalizes several state of the art metrics and identifies three essential ground concepts at the roots of noveltyand diversity: choice, discovery and relevance, upon which the framework is built.
An Adaptation of the Vector-Space Model for Ontology-Based Information Retrieval
- P. Castells, Miriam Fernández, D. Vallet
- Computer ScienceIEEE Transactions on Knowledge and Data…
- 1 February 2007
A model for the exploitation of ontology-based knowledge bases to improve search over large document repositories and is combined with conventional keyword-based retrieval to achieve tolerance to knowledge base incompleteness.
Novelty and Diversity in Recommender Systems
An overview of the main contributions to this area in the field of recommender systems, and seeks to relate them together in a unified view, analyzing the common elements underneath the different forms under which novelty and diversity have been addressed, and identifying connections to closely related work on diversity in other fields.
Coverage, redundancy and size-awareness in genre diversity for recommender systems
- S. Vargas, L. Baltrunas, Alexandros Karatzoglou, P. Castells
- Computer ScienceRecSys '14
- 6 October 2014
A new Binomial framework for defining genre diversity in recommender systems that takes into account three key properties: genre coverage, genre redundancy and recommendation list size-awareness is proposed.
Automatic Assignment of Wikipedia Encyclopedic Entries to WordNet Synsets
An approach taken for automatically associating entries from an on-line encyclopedia with concepts in an ontology or a lexical semantic network is described, which will be applied to enriching ontologies with encyclopedic knowledge.
Declarative interface models for user interface construction tools: the MASTERMIND approach
- Pedro A. Szekely, N. Sukaviriya, P. Castells, Jeyakumar Muthukumarasamy, Ewald Salcher
- Computer ScienceEHCI
- 1 August 1995
Model-based programming provides an alternative new paradigm that describes the tasks that users are expected to accomplish with a systems, the functional capabilities of a system, the style and requirements of the interface, the characteristics and preferences of the users, and the I/O techniques supported by the delivery platform.
Improving sales diversity by recommending users to items
This work explores the inversion of the recommendation task as a means to enhance sales diversity - and indirectly novelty - by selecting which users an item should be recommended to instead of the other way around, and addresses the inverted task by inverting the rating matrix.
An empirical comparison of social, collaborative filtering, and hybrid recommenders
- Alejandro Bellogín, Iván Cantador, Fernando Díez, P. Castells, Enrique Chavarriaga
- Computer ScienceTIST
A coverage metric is proposed that uncovers and compensates for the incompleteness of performance evaluations based only on precision and is used together with precision metrics in an empirical comparison of several social, collaborative filtering, and hybrid recommenders.
Semantically enhanced Information Retrieval: An ontology-based approach
A study of heterogeneity in recommendations for a social music service
The obtained results show that, in Last.fm, social tagging and explicit social networking information provide effective and heterogeneous item recommendations, and give first insights on the feasibility of exploiting the above non performance recommendation characteristics by hybrid approaches.