A hybrid recommendation approach for hierarchical items

Recommender systems aim to recommend items that are likely to be of interest to the user. In many business situations, complex items are described by hierarchical tree structures, which contain rich semantic information. To recommend hierarchical items accurately, the semantic information of the hierarchical tree structures must be considered comprehensively. In this study, a new hybrid recommendation approach for complex hierarchical tree structured items is proposed. In this approach, a comprehensive semantic similarity measure model for hierarchical tree structured items is developed. It is integrated with the traditional item-based collaborative filtering approach to generate recommendations. © 2010 IEEE

A dynamic recommender system as reinforcement for personalized education by a fuzzly linguistic web system

Information Technology and Quantitative Management (ITQM 2015)The seek of a personalized and quality education is the objective of Bologna process, but to carry out this task has a major economic impact. To soften this impact, one possible solution is to make use of recommender systems, which have already been introduced in several academic fields. In this paper, we present AyudasCBI, a novel fuzzy linguistic Web system that uses a recommender system to provide personalized activities to students to reinforce their individualized education. This system can be used in order to aid professors to provide students with a personalized monitoring of their studies with less effort. To prove the system, we conduct a study involving some students, aiming at measuring their performance. The results obtained proved to be satisfactory compared with the rest of the students who did not take part of the study.Projects TIC-5991 and TIN2013-40658-

Latent Dirichlet Allocation (LDA) for improving the topic modeling of the official bulletin of the spanish state (BOE)

Since Internet was born most people can access fully free to a lot sources of information. Every day a lot of web pages are created and new content is uploaded and shared. Never in the history the humans has been more informed but also uninformed due the huge amount of information that can be access. When we are looking for something in any search engine the results are too many for reading and filtering one by one. Recommended Systems (RS) was created to help us to discriminate and filter these information according to ours preferences. This contribution analyses the RS of the official agency of publications in Spain (BOE), which is known as "Mi BOE'. The way this RS works was analysed, and all the meta-data of the published documents were analysed in order to know the coverage of the system. The results of our analysis show that more than 89% of the documents cannot be recommended, because they are not well described at the documentary level, some of their key meta-data are empty. So, this contribution proposes a method to label documents automatically based on Latent Dirichlet Allocation (LDA). The results are that using this approach the system could recommend (at a theoretical point of view) more than twice of documents that it now does, 11% vs 23% after applied this approach

A fuzzy tree similarity based recommendation approach for telecom products

Due to the huge product assortments and complex descriptions of telecom products, it is a great challenge for customers to select appropriate products. A fuzzy tree similarity based hybrid recommendation approach is proposed to solve this issue. In this study, fuzzy techniques are used to deal with the various uncertainties existing within the product and customer data. A fuzzy tree similarity measure is developed to evaluate the semantic similarity between tree structured products or user profiles. The similarity measures for items and users both integrate the collaborative filtering (CF) and semantic similarities. The final recommendation hybridizes item-based and user-based CF recommendation techniques. A telecom product recommendation case study is given to show the effectiveness of the proposed approach. © 2013 IEEE

A Linguistic Recommender System For University Digital Libraries To Help Users In Their Research Resources Accesses

The Web is one of the most important information media and it is influencing in the development of other media, as for example, newspapers, journals, books, libraries, etc. Moreover, in recent days people want to communicate and collaborate. So, libraries must develop services for connecting people together in information environments. Then, the library staff needs automatic techniques to facilitate that a great number of users can access to a great number of resources. Recommender systems are tools whose objective is to evaluate and filter the great amount of information available on the Web. We present a model of a fuzzy linguistic recommender system to help University Digital Library users in their research resources accesses. This system recommends researchers specialized and complementary resources in order to discover collaboration possibilities to form multi-disciplinaryy groups. In this way, this system increases social collaboration possibilities in a university framework and contributes to improve the services provided by a University Digital Library

TEST ENVIRONMENT FOR INTERACTIVE MOBILE TV SERVICES BASED ON DVB-H

La televisión móvil basada en el estándar DVB-H no ha tenido una aceptación semejante a la de la televisión convencional, lo anterior debido a dificultades propias del estándar y a características de despliegue del servicio. Las problemáticas de la televisión móvil se resumen en: necesidad de una red bidireccional alterna o canal de retorno para el consumo de servicios, el tiempo de salto de un canal a otro, el bajo tiempo promedio de uso diario de la televisión móvil, los pocos dispositivos que soportan el estándar y la no existencia de un middleware para el desarrollo de aplicaciones interactivas de televisión móvil. El presente artículo plantea un entorno de despliegue y pruebas para servicios interactivos de televisión móvil, que busca responder a los anteriores problemas. El entorno propuesto tiene en cuenta aspectos como la convergencia de servicios en redes WLAN, el uso falcsonomías para recomendación de contenidos y la red celular como canal de retorno o canal de consumo de servicios.Mobile TV based on DVB-H has not had an acceptance similar to the conventional television, above due to difficulties of the standard and the characteristics of service deployment. The problems of mobile TV are summarized in: the need to have a return channel for the consumption of services, the time to switch from one channel to another, the few devices that support the standard and the absence of a middleware for the development of Mobile TV interactive applications. This paper presents a testing and deployment environment for interactive mobile TV services, which wants to respond to the above problems. The proposed environment takes into account aspects such as: the convergence of services on WLANs, the use falksonomies for content recommendation and the cellular network as a return channel or channel service consumption

SINVLIO: using semantics and fuzzy logic to provide individual investment portfolio recommendations

Portfolio selection addresses the problem of how to diversify investments in the most efficient and profitable way possible. Portfolio selection is a field of study that has been broached from several perspectives, including, among others, recommender systems. This paper presents SINVLIO (Semantic INVestment portfoLIO), a tool based on semantic technologies and fuzzy logic techniques that recommends investments grounded in both psychological aspects of the investor and traditional financial parameters of the investments. The results are very encouraging and reveal that SINVLIO makes good recommendations, according to the high degree of agreement between SINVLIO and expert recommendationsThis work is supported by the Spanish Ministry of Industry, Tourism, and Commerce under the projects SONAR2 (TSI-020100-2008-665) and the Spanish Ministry of Science and Innovation under the project “FINANCIAL LINKED OPEN DATA REASONING AND MANAGEMENT FOR WEB SCIENCE” (TIN2011-27405).Publicad

Information-Based Neighborhood Modeling

Since the inception of the World Wide Web, the amount of data present on websites and internet infrastructure has grown exponentially that researchers continuously develop new and more efficient ways of sorting and presenting information to end-users. Particular websites, such as e-commerce websites, filter data with the help of recommender systems. Over the years, methods have been developed to improve recommender accuracy, yet developers face a problem when new items or users enter the system. With little to no information on user or item preferences, recommender systems struggle generating accurate predictions. This is the cold-start problem. Ackoff defines information as data structured around answers to the question words: what, where, when, who and how many. This paper explores how Ackoff’s definition of information might improve accuracy and alleviate cold-start conditions when applied to the neighborhood model of collaborative filtering (Ackoff, 1989, p. 3)

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse