Mining Frequent Generalized Patterns for Web Personalization in the presence of Taxonomies

The Web is a continuously evolving environment, since its content is updated on a regular basis. As a result, the traditional usage-based approach to generate recommendations that takes as input the navigation paths recorded on the Web page level, is not as effective. Moreover, most of the content available online is either explicitly or implicitly characterized by a set of categories organized in a taxonomy, allowing the page-level navigation patterns to be generalized to a higher, aggregate level. In this direction, the authors present the Frequent Generalized Pattern (FGP) algorithm. FGP takes as input the transaction data and a hierarchy of categories and produces generalized association rules that contain transaction items and/or item categories. The results can be used to generate association rules and subsequently recommendations for the users. The algorithm can be applied to the log files of a typical Web site; however, it can be more helpful in a Web 2.0 application, such as a feed aggregator or a digital library mediator, where content is semantically annotated and the taxonomic nature is more complex, requiring us to extend FGP in a version called FGP+. The authors experimentally evaluate both algorithms using Web log data collected from a newspaper Web site

Desambiguación Verbal Automática. Un estudio sobre el rendimiento de la información semántica argumental

Treballs Finals de Grau de Lingüística. Facultat de Filologia. Universitat de Barcelona, Curs: 2015-2016, Tutor: Carme Junyent Figueras. Director: Irene Castellón MasallesUna de las tareas fundamentales todavía hoy pendientes de resolución en el ámbito del Procesamiento del Lenguaje Natural es la Desambiguación Semántica Automática (DSA); especialmente la tarea específica de Desambiguación Verbal Automática (DVA). En la presente investigación se aborda esta cuestión del modo siguiente: en primer lugar, se realiza una descripción del panorama actual en DSA, las aproximaciones posibles a esta tarea y los retos que plantea el desarrollo de la DVA. En segundo lugar, se lleva a cabo una tarea experimental con la finalidad de comprobar la viabilidad de una aproximación a la DVA basada en la información semántica de los argumentos verbales. Los buenos resultados obtenidos indicarían la necesidad de tener en cuenta este tipo de información en futuras propuestas de DVA. Palabras clave: Semántica; Procesamiento del Lenguaje Natural; Desambiguación Verbal Automática; Aprendizaje AutomáticoOne of the key tasks still pending in the field of Natural Language Processing is Word Sense Disambiguation (WSD); especially the specific task of Verb Sense Disambiguation (VSD). In the present study this issue is addressed as follows: in the first place, a description of the current situation in WSD, the possible approaches to this task and the challenges posed by the development of VSD is provided. In the second place, an experimental task is performed in order to test the feasibility of an approach to VSD based on semantic information about verbal arguments. The good results obtained indicate the need to take into account this information in future proposals for VSD. Keywords: Semantics; Natural Language Processing; Verb Sense Disambiguation; Machine Learnin