Automatic Annotation and Semantic Search from Protégé

Semantic search has been one of the major envisioned benefits of the Semantic Web since its emergence in the late 90’s [1]. Our demo shows a proposal towards this goal. One way to view a semantic search engine is as a tool that gets formal queries (e.g. in RDQL, RQL, SPARQL, or the like) from a client, executes them against an ontology-based knowledge base, and returns tuples of ontology values (resources) that satisfy the query [2]. While this conception of semantic search brings enormous advantages already, our work aims at taking a step beyond this. In our view of Information Retrieval in the Semantic Web, a search engine returns documents, rather than (or in addition to) exact values, in response to user queries. The engine should rank the documents, according to concept-based relevance criteria. The overall retrieval process is illustrated in Figure 1 (see [3] for more details of our research)

The quest for information retrieval on the semantic web

Semantic search has been one of the motivations of the Semantic Web since it was envisioned. We propose a model for the exploitation of ontology-based KBs to improve search over large document repositories. The retrieval model is based on an adaptation of the classic vector-space model, including an annotation weighting algorithm, and a ranking algorithm. Semantic search is combined with keyword-based search to achieve tolerance to KB incompleteness. Our proposal has been tested on corpora of significant size, showing promising results with respect to keyword-based search, and providing ground for further analysis and research

Intractable problems in novelty and diversity

Versión electrónica de la ponencia presentada en la XVI Jornadas de Ingeniería del Software y de Bases de Datos (JISBD 2011), celebrada en 2011 en A CoruñaInformation retrieval’s basic problem is retrieving a set of documents relevant for a given query. Here, we present three classes of methods that appeared in the liteature, as well as a new one, which is an improvement of the one the three, to retrieve result sets that, in addition to relevance, try to maximize diversity and novelty. We analyze the complexity of these problems and show that whenever relevance, diversity, and novelty are considered together, the methods are all NP-complete.This work was supported in part by the Ministerio de Educaci´on y Ciencia under the grant N. MEC TIN2008-06566-C04-02

An evaluation of novelty and diversity based on fuzzy logic

Also published online by CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) Proceedings of the Workshop on Novelty and Diversity in Recommender Systems, DiveRS 2011Information retrieval systems are based on an estimation or prediction of the relevance of documents for certain topics associated to a query or, in the case of recommendation systems, for a certain user profile. Most systems use a graded relevance estimation (a.k.a. relevance status value), that is, a real value r(d,τ ) ∈ [0, 1] for the relevance of document d with respect to topic τ . In retrieval systems based on the Probability Ranking Principle [9], this value has a probabilistic interpretation, that is, r(d, τ ) is equivalent (in rank) to the probability that a user will consider the document relevant. We contend in this paper for an alternative interpretation, where the value r(d, τ ) is considered as the fuzzy truth value of the statement “d is relevant for τ”. We develop and evaluate two measures that determine the quality of a result set in terms of diversity and novelty based on this fuzzy interpretation

Rank and relevance in novelty and diversity metrics for recommender systems

This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in RecSys '11 Proceedings of the fifth ACM conference on Recommender systems, http://dx.doi.org/10.1145/2043932.2043955The Recommender Systems community is paying increasing attention to novelty and diversity as key qualities beyond accuracy in real recommendation scenarios. Despite the raise of interest and work on the topic in recent years, we find that a clear common methodological and conceptual ground for the evaluation of these dimensions is still to be consolidated. Different evaluation metrics have been reported in the literature but the precise relation, distinction or equivalence between them has not been explicitly studied. Furthermore, the metrics reported so far miss important properties such as taking into consideration the ranking of recommended items, or whether items are relevant or not, when assessing the novelty and diversity of recommendations. We present a formal framework for the definition of novelty and diversity metrics that unifies and generalizes several state of the art metrics. We identify three essential ground concepts at the roots of novelty and diversity: choice, discovery and relevance, upon which the framework is built. Item rank and relevance are introduced through a probabilistic recommendation browsing model, building upon the same three basic concepts. Based on the combination of ground elements, and the assumptions of the browsing model, different metrics and variants unfold. We report experimental observations which validate and illustrate the properties of the proposed metrics.This work is supported by the Spanish Government (TIN2011- 28538-C02-01), and the Government of Madrid (S2009TIC-1542)

e-Portfolio: Java technology for financial applications on the Internet

This is an electronic version of the paper presented at the WebNet 2001 World Conference on the WWW and Internet, held in Orlando on 2001The rapid introduction of the Internet technologies in the financial sector is leading to profound changes affecting both financial service companies and private investors. Web-based technologies have transfigured our concept of information availability, and are transforming the way customers and service providers communicate and relate to each other as well, posing new organizational and computational challenges. A new generation of financial applications is needed that a) help users in accessing the right information in an understandable form, despite the size and complexity of information sources, b) are readily available from handy standard connection points, c) do not impose heavy or too restrictive platform requirements on the user, and d) assure transparent, reliable and secure transactions for the client. In this paper we describe e-Portfolio, a Java-based financial application that gives assistance in the choice of an optimal investment strategy according to an investor's profile. e-Portfolio’s highly portable, interoperable, and reusable components result in a very flexible architecture that can be accommodated to different business settings and requirements

Building emergent social networks and group profiles by semantic user preference clustering

This is an electronic version of the paper presented at the International Workshop on Semantic Network Analysis (SNA 2006) at the European Semantic Web Conference (ESWC 2006), held in Budva on 2006This paper presents a novel approach to automatic semantic social network construction based on semantic user preference clustering. Considering a number of users, each of them with an associated ontology-based profile, we propose a strategy that clusters the concepts of the reference ontology according to user preferences of these concepts, and then determines which clusters are more appropriate to the users. The resultant user clusters can be merged into individual group profiles, automatically defining a semantic social network suitable for use in collaborative and recommendation environments.This research was supported by the European Commission (FP6-027685 – MESH), and the Spanish Ministry of Science and Education (TIN2005-06885). The expressed content is the view of the authors but not necessarily the view of the MESH project as a whole

Enriching ontological user profiles with tagging history for multi-domain recommendations

Many advanced recommendation frameworks employ ontologies of various complexities to model individuals and items, providing a mechanism for the expression of user interests and the representation of item attributes. As a result, complex matching techniques can be applied to support individuals in the discovery of items according to explicit and implicit user preferences. Recently, the rapid adoption of Web2.0, and the proliferation of social networking sites, has resulted in more and more users providing an increasing amount of information about themselves that could be exploited for recommendation purposes. However, the unification of personal information with ontologies using the contemporary knowledge representation methods often associated with Web2.0 applications, such as community tagging, is a non-trivial task. In this paper, we propose a method for the unification of tags with ontologies by grounding tags to a shared representation in the form of Wordnet and Wikipedia. We incorporate individuals' tagging history into their ontological profiles by matching tags with ontology concepts. This approach is preliminary evaluated by extending an existing news recommendation system with user tagging histories harvested from popular social networking sites

An EUD Approach for Making MBUI Practical

Proceedings of the First International Workshop on Making model-based user interface design practical: usable and open methods and tools. Funchal, Madeira, Portugal, January.13, 2004Also published online by CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073)In this paper, we present our perspective on Model-Based User Interfaces (hereafter MBUI) paradigm and provide with our experience in this area combining high-level knowledge-based data models (i.e. ontologies) and reverse engineering processes to carry through a pragmatic MBUI vision. Our approach is based on using End-User Development (hereafter EUD) techniques (i.e. Programming by Example) to enable the user to carry out editing tasks in a MBUI environment. This advocates an EUD-for-MBUI approach, where the system avoids the user from having to deal with interface specification languages.The work reported in this paper is being supported by the Spanish Ministry of Science and Technology (MCyT), project number TIC2002-194