Information Retrieval and Recommender Systems

J.UCS Special Issue

Nowadays Information Retrieval (IR) [Baeza-Yates and Ribeiro-Neto 1999] has become a vital part of the daily activity of any web user: the difficulty of finding relevant information in the largest repository of knowledge makes imperative the use of IR models and techniques. However, the users are increasingly expecting answers to their information needs without the formulation any explicit query. In this context, active Information Filtering systems have taken a leading role. The most common type of information filters are Recommender Systems (RS) [Ricci et al. 2010]. Both fields IR and RS are commonly assumed as two sides of the same coin [Belkin and Croft 1992] because the final objective of both is the same: provide relevant information to the users.

Therefore, we devoted this issue to Information Retrieval and Recommender Systems methods. This special issue includes extended version of selected papers presented at the Spanish Conference on Information Retrieval 2014 (CERI 2014) as well as scientific papers from the international research community in Information Retrieval and Recommendation.

The Spanish Conference on Information Retrieval is the forum where academics, researchers and entrepreneurs from the Information Retrieval (IR) field can meet and exchange experiences. The objective is to provide a space where not only national research groups and companies, but also international research groups, can show the main advances in IR.

The organizers of the CERI 2014 decided to publish an extended version of some papers and, at the same time, open the submission to new articles from other researchers, with the aim to congregate different research works from a wide range of knowledge areas but always focused on relevant problems of IR and Recommendation. A total of 14 submissions were received and followed a strict peer reviewing process, where each article has been reviewed by at least three reviewers. The reviewing panel was composed of 35 international scientists, both from the academic and industry. At the end of the reviewing process, 8 full papers were accepted.

The topics covered in this special issue include: advances in cross-language source code similarity by Flores et al., optimizations in the parameter selection for IR systems by Bigot et al., a design pattern IR system by Bouassida et al., advances in the statistical analysis of IR system parameters by Ayter et al., power consumption optimizations of replicated IR systems by Freire et al., scalable architectures for distributed recommendation systems by Valcarce et al., an IR system applied to medicine by Betina and Mahalakshmi, and advances in the performance evaluation of the recommendation systems by Corona et al.

Finally, we would like to express our gratitude to all the authors as well as to all the reviewers that so generously collaborated in the realization of this special issue. Moreover, we would like to specially thank the support of the Rede Galega de Procesamento da Linguaxe e Recuperacin de Informacin (R2014/034) for its contribution in the publication of this special issue and to the Spanish Society of Information Retrieval (SERI), which supports and encourages research in Information Retrieval in Spanish companies and institutions.

References

[Baeza-Yates and Ribeiro-Neto 1999] Baeza-Yates, R. A., Ribeiro-Neto, B.: Modern Information Retrieval; Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA, 1999.

[Belkin and Croft 1992] Belkin, N. J., Croft, W. B.: "Information filtering and information retrieval: Two sides of the same coin?"; Commun. ACM; 35 (1992), 12, 29-38.

[Ricci et al. 2010] Ricci, F., Rokach, L., Shapira, B., Kantor, P. B.: Recommender Systems Handbook; Springer-Verlag New York, Inc., New York, NY, USA, 2010; 1st edition.