OBOME - Ontology based opinion mining in UBIPOL

Ontologies have a special role in the UBIPOL system, they help to structure the policy related context, provide conceptualization for policy domain and use in the opinion mining process. In this work we presented a system called Ontology Based Opinion Mining Engine (OBOME) for analyzing a domain-specific opinion corpus by first assisting the user with the creation of a domain ontology from the corpus. We determined the polarity of opinion on the various domain aspects. In the former step, the policy domain aspect has are identified (namely which policy category is represented by the concept). This identification is supported by the policy modelling ontology, which describe the most important policy – related classes and structure. Then the most informative documents from the corpus are extracted and asked the user to create a set of aspects and related keywords using these documents. In the latter step, we used the corpus specific ontology to model the domain and extracted aspect-polarity associations using grammatical dependencies between words. Later, summarized results are shown to the user to analyze and store. Finally, in an offline process policy modeling ontology is updated

A roadmap for semantifying recommender systems using preference management

25th International Symposium on Computer and Information Sciences, ISCIS 2010 -- 22 September 2010 through 24 September 2010 -- London -- 82255The work developed in this paper presents an innovative solution in the field of recommender systems. Our aim is to create integration architecture for improving recommendation effectiveness that obtains user preferences found implicitly in domain knowledge. This approach is divided into four steps. The first step is based on semantifying domain knowledge. In this step, domain ontology will be analyzed. The second step is to define an innovative hybrid recommendation algorithm based upon collaborative filtering and content filtering. The third step is based on preference modeling approach. And in the fourth step preference model and recommendation algorithm will be integrated. Finally, this work will be realized on Netflix movie data source. © 2011 Springer Science+Business Media B.V

An extension of ontology based databases to handle preferences

ICEIS 2009 - 11th International Conference on Enterprise Information Systems -- 6 May 2009 through 10 May 2009 -- Milan -- 79065Ontologies have been defined to make explicit the semantics of data. With the emergence of the SemanticWeb, the amount of ontological data (or instances) available has increased. To manage such data, Ontology Based DataBases (OBDBs), that store ontologies and their instance data in the same repository have been proposed. These databases are associated with exploitation languages supporting description, querying, etc. on both ontologies and data. However, usually queries return a big amount of data that may be sorted in order to find the relevant ones. Moreover, in the current, few approaches considering user preferences when querying have been developed. Yet this problem is fundamental for many applications especially in the e-commerce domain. In this paper, we first propose an extension of an existing OBDB, called OntoDB through extension of their ontology model in order to support semantic description of preferences. Secondly, an extension of an ontology based query language, called OntoQL defined on OntoDB for querying ontological data with preferences is presented. Finally, an implementation of the proposed extensions are described

Ontology-based database approach for handling preferences

Information systems now manage huge amount of data. Users are overwhelmed by the numerous results provided in response to their requests. These results must often be sorted and filtered in order to be usable. Moreover, the "one size fits all" approach has shown its limitation for information searching in many applications, particularly in the e-commerce domain. The capture and exploitation of user preferences have been proposed as a solution to overcome this problem. However, the existing approaches usually define preferences for a particular application. Thus, it is difficult to share and reuse the handled preferences in other contexts. In this chapter, we propose a sharable, formal and generic model to represent user's preferences. The model gathers several preferences models proposed in the Database and Semantic Web communities. The novelty of our approach is that the defined preferences are attached to the ontologies which describe the semantic of the data manipulated by the applications. Moreover, the proposed model offers a persistence mechanism and a dedicated language; it is implemented using Ontology-Based Databases (OBDB) system extended in order to take into account preferences. OBDB manage both ontologies and the data instances. The preference model is formally defined using the EXPRESS data modelling language which ensures us a free ambiguity definition and the approach is illustrated through a case study in the tourism domain. © 2010, IGI Global