Enriqueciendo revisiones de usuarios mediante un sistema de extracción de opiniones

Web sites based on User-Generated Content (UGC) have a potentially valuable applicability in a number of fields. In this work we carry out a study of the usefulness of these systems from the point of view of detecting the perception expressed by users about services or items. We have compiled and analyzed opinions shared by users on TripAdvisor focusing on two aspects: the structured and the unstructured data. We perform a quantitative and a qualitative analysis of the information extracted by an opinion extraction system from our dataset, being the last one especially interesting since it provides valuable knowledge about the strong and weak points of hotels according to user perceptions, going beyond the structured data. Finally, we provide a study on the complementarity of the knowledge extracted from both, the textual opinions and the structured data, observing a noticeable increment of the amount of information available with the conjunction of both sources.Las webs basadas en el contenido generado por usuarios (UGC) tienen una aplicabilidad potencial en un gran número de campos. En este trabajo realizamos un estudio de la utilidad de estos sistemas para determinar la percepción de los usuarios expresada en sus opiniones sobre productos o servicios. Para ello, hemos compilado y analizado opiniones compartidas por usuarios en TripAdvisor, centrándonos en dos aspectos: el contenido estructurado y el no estructurado. Hemos realizado un análisis cuantitativo y cualitativo de la información extraída por un sistema de minería de opiniones, siendo este último especialmente interesante ya que ofrece información valiosa sobre los puntos fuertes y débiles de los hoteles según la percepción de los usuarios, yendo más allá de la información estructurada. Por último, hemos realizado un estudio de la complementariedad de la información estructurada y la no estructurada, observando un gran incremento de la cantidad de información disponible conjuntando ambas.This work has been partially funded by the research projects AORESCU (P11-TIC-7684, Consejería de Innovación, Ciencia y Empresas, Junta de Andalucía), DOCUS (TIN2011-14726-E, Ministerio de Ciencia e Innovación) and ACOGEUS (TIN2012-38536-C03-02, Ministerio de Economía y Competitividad)

Adaptive learning program for developing employability skills

The paper aims to demonstrate the benefits of adaptive learning technologies as a viable alternative to time consuming tutor led individual support. It proposes to reveal how adaptive learning interventions can be effective in enriching student learning while targeting precise areas of development. This review will compile evidence on the nature and extent of Adaptive Learning tools used to develop employability skills among Higher Education institutions. This will be specifically for students undergoing studies at the graduate level. Given the short time available, a scoping study framework will be used to examine the scope of carrying out a full systematic review or identifying gaps in existing literature (Arksey and O’Malley, 2005). This design follows the general principles of a systematic review by following pre‐specified methods to reduce the risk of bias by selecting favourable studies, and extracting and analysing data that backs a particular hypothesis. That is, the methods are determined a priori, and are transparent and replicable

A new approach to ontology-based semantic modelling for opinion mining

With the fast growth of World Wide Web 2.0, a great number of opinions about a variety of products have been published in blogs, forums, and social networks. Opinion mining tools are needed to enable users to efficiently process a large number of reviews found online, in order to determine the underlying opinions. This paper presents a new methodology for semantic modelling of the domain knowledge for opinion mining. In particular, the new methodology focuses on modelling the domain knowledge in such a way that it can be translated to a formal ontology, which can then be automatically enriched with ground facts obtained from public Linked Open Data resources. The methodology also considers procedures to link between the formal ontology and Natural Language Processing. Our approach successfully enriches the ontology with the relevant ground facts. This ontology can then be used to perform a variety of data mining tasks including sentiment analysis and information retrieval

Catalyst: Piloting Capabilities for more Transparent Text Analytics

The surge and value of unstructured text is attracting substantial research and industry attention. Subsequently we are witnessing novel techniques and algorithms that are performing increasingly sophisticated text mining tasks. However the majority of such techniques are opaque, making it hard to trace the provenance of the analytical task on hand. We propose Catalyst, a framework to automatically transform, enrich and expose text into a linked graph-based layer to enable more transparent processing and access to the text elements. In brief, Catalyst extracts text dependencies, performs sentiment analysis, detects semantic relatedness, and links the text elements into a semantic triple-store that enables an easy access to the text entities through direct query functionalities. We plan to evaluate the performance of Catalyst by processing a dataset of user reviews around the dimensions of an evaluation model deployed in the context of e-government services

Applying Supervised Opinion Mining Techniques on Online User Reviews

In recent years, the spectacular development of web technologies, lead to an enormous quantity of user generated information in online systems. This large amount of information on web platforms make them viable for use as data sources, in applications based on opinion mining and sentiment analysis. The paper proposes an algorithm for detecting sentiments on movie user reviews, based on naive Bayes classifier. We make an analysis of the opinion mining domain, techniques used in sentiment analysis and its applicability. We implemented the proposed algorithm and we tested its performance, and suggested directions of development