An application of the FIS-CRM model to the FISS metasearcher: Using fuzzy synonymy and fuzzy generality for representing concepts in documents

AbstractThe main objective of this work is to improve the quality of the results produced by the Internet search engines. In order to achieve it, the FIS-CRM model (Fuzzy Interrelations and Synonymy based Concept Representation Model) is proposed as a mechanism for representing the concepts (not only terms) contained in any kind of document. This model, based on the vector space model, incorporates a fuzzy readjustment process of the term weights of each document. The readjustment lies on the study of two types of fuzzy interrelations between terms: the fuzzy synonymy interrelation and the fuzzy generality interrelations (“broader than” and “narrower than” interrelations). The model has been implemented in the FISS metasearcher (Fuzzy Interrelations and Synonymy based Searcher) that, using a soft-clustering algorithm (based on the SISC algorithm), dynamically produces a hierarchical structure of groups of “conceptually related” documents (snippets of web pages, in this case)

An automated and fuzzy approach for semantically annotating services

© 2015 IEEE. In the recent past, semantic technologies have played an significant role in service retrieval and service querying. Annotating services semantically enables machines to understand the purpose of services and can further assist in intelligent and precise service retrieval, selection and composition. A key issue in semantically annotating services is the manual nature of service annotation. Manual service annotation requires a large amount of time and updating happens infrequently, hence annotations may get out-of-date due to service description changes. Although some researchers have studied semantic service annotation, they have only focused on web services not business service information. Moreover, their approaches are semi-automated, and still require service providers to select appropriate service annotations. In this paper, we propose a completely automated semantic annotation approach for e-services. The aim of this paper is to semantically annotate a service to relevant service concepts in domain-specific ontologies. Services and service concepts are represented by an extended VSM model, based on fuzzy rules. Then, we link a service to a concept, based on the similarity value of the representing vectors. We found during the experimentation process that the performances of the proposed approach and the VSM-based approach were quite similar and, as a result, developed a system to retrieve services that are annotated to relevant concepts. Experiments using a high service retrieval threshold demonstrated a retrieval approach based on extended VSM annotation performed much better than an approach based on VSM annotation

Búsqueda eficaz de información en la web

En este trabajo se describe someramente lo que es un Sistema de Recuperación de Información, para posteriormente poder profundizar en algunos aspectos específicos. Se presentan las herramientas de búsqueda Web más usadas actualmente, haciendo especial hincapié en los buscadores y en los metabuscadores, con el fin de proporcionar ciertos “trucos” para ayudar a mejorar nuestro acceso y búsqueda en los contenidos de la Web (por ejemplo explicando el uso de algunos operadores de búsqueda, cómo funcionan los algoritmos de ranking, como mejorar la posición de una página Web en los buscadores o cuáles son las peculiaridades de las arquitecturas computacionales de algunos motores de búsqueda). Finalmente, se propone el desarrollo y pruebas de mecanismos más “inteligentes” de acceso, búsqueda, gestión y recuperación de información y conocimiento contenidos en la Web. Para ello se muestra el uso de técnicas avanzadas de Inteligencia Artificial, en particular aquellas más cercanas a la manipulación del lenguaje natural y al comportamiento humano.XV Escuela Internacional de Informática, realizada durante el XVII Congreso Argentino de Ciencia de la Computación (CACIC 2011).Red de Universidades con Carreras en Informática (RedUNCI

Búsqueda eficaz de información en la web

En este trabajo se describe someramente lo que es un Sistema de Recuperación de Información, para posteriormente poder profundizar en algunos aspectos específicos. Se presentan las herramientas de búsqueda Web más usadas actualmente, haciendo especial hincapié en los buscadores y en los metabuscadores, con el fin de proporcionar ciertos “trucos” para ayudar a mejorar nuestro acceso y búsqueda en los contenidos de la Web (por ejemplo explicando el uso de algunos operadores de búsqueda, cómo funcionan los algoritmos de ranking, como mejorar la posición de una página Web en los buscadores o cuáles son las peculiaridades de las arquitecturas computacionales de algunos motores de búsqueda). Finalmente, se propone el desarrollo y pruebas de mecanismos más “inteligentes” de acceso, búsqueda, gestión y recuperación de información y conocimiento contenidos en la Web. Para ello se muestra el uso de técnicas avanzadas de Inteligencia Artificial, en particular aquellas más cercanas a la manipulación del lenguaje natural y al comportamiento humano.XV Escuela Internacional de Informática, realizada durante el XVII Congreso Argentino de Ciencia de la Computación (CACIC 2011).Red de Universidades con Carreras en Informática (RedUNCI

Digital Transformation and Digital Strategy roadmap: the growing importance of CRM.

In the globalized we are living. The market is characterized by high competition the only thing companies to customers and gain a competitive advantage is to focus on customers. The aimed this work is to analyse CRM under a strategical and technological point of view. A special focus is given to influence of internet and social media thraugh big data on CRM. At the and a business case is presente

Using spatiotemporal patterns to qualitatively represent and manage dynamic situations of interest : a cognitive and integrative approach

Les situations spatio-temporelles dynamiques sont des situations qui évoluent dans l’espace et dans le temps. L’être humain peut identifier des configurations de situations dans son environnement et les utilise pour prendre des décisions. Ces configurations de situations peuvent aussi être appelées « situations d’intérêt » ou encore « patrons spatio-temporels ». En informatique, les situations sont obtenues par des systèmes d’acquisition de données souvent présents dans diverses industries grâce aux récents développements technologiques et qui génèrent des bases de données de plus en plus volumineuses. On relève un problème important dans la littérature lié au fait que les formalismes de représentation utilisés sont souvent incapables de représenter des phénomènes spatiotemporels dynamiques et complexes qui reflètent la réalité. De plus, ils ne prennent pas en considération l’appréhension cognitive (modèle mental) que l’humain peut avoir de son environnement. Ces facteurs rendent difficile la mise en œuvre de tels modèles par des agents logiciels. Dans cette thèse, nous proposons un nouveau modèle de représentation des situations d’intérêt s’appuyant sur la notion des patrons spatiotemporels. Notre approche utilise les graphes conceptuels pour offrir un aspect qualitatif au modèle de représentation. Le modèle se base sur les notions d’événement et d’état pour représenter des phénomènes spatiotemporels dynamiques. Il intègre la notion de contexte pour permettre aux agents logiciels de raisonner avec les instances de patrons détectés. Nous proposons aussi un outil de génération automatisée des relations qualitatives de proximité spatiale en utilisant un classificateur flou. Finalement, nous proposons une plateforme de gestion des patrons spatiotemporels pour faciliter l’intégration de notre modèle dans des applications industrielles réelles. Ainsi, les contributions principales de notre travail sont : Un formalisme de représentation qualitative des situations spatiotemporelles dynamiques en utilisant des graphes conceptuels. ; Une approche cognitive pour la définition des patrons spatio-temporels basée sur l’intégration de l’information contextuelle. ; Un outil de génération automatique des relations spatiales qualitatives de proximité basé sur les classificateurs neuronaux flous. ; Une plateforme de gestion et de détection des patrons spatiotemporels basée sur l’extension d’un moteur de traitement des événements complexes (Complex Event Processing).Dynamic spatiotemporal situations are situations that evolve in space and time. They are part of humans’ daily life. One can be interested in a configuration of situations occurred in the environment and can use it to make decisions. In the literature, such configurations are referred to as “situations of interests” or “spatiotemporal patterns”. In Computer Science, dynamic situations are generated by large scale data acquisition systems which are deployed everywhere thanks to recent technological advances. Spatiotemporal pattern representation is a research subject which gained a lot of attraction from two main research areas. In spatiotemporal analysis, various works extended query languages to represent patterns and to query them from voluminous databases. In Artificial Intelligence, predicate-based models represent spatiotemporal patterns and detect their instances using rule-based mechanisms. Both approaches suffer several shortcomings. For example, they do not allow for representing dynamic and complex spatiotemporal phenomena due to their limited expressiveness. Furthermore, they do not take into account the human’s mental model of the environment in their representation formalisms. This limits the potential of building agent-based solutions to reason about these patterns. In this thesis, we propose a novel approach to represent situations of interest using the concept of spatiotemporal patterns. We use Conceptual Graphs to offer a qualitative representation model of these patterns. Our model is based on the concepts of spatiotemporal events and states to represent dynamic spatiotemporal phenomena. It also incorporates contextual information in order to facilitate building the knowledge base of software agents. Besides, we propose an intelligent proximity tool based on a neuro-fuzzy classifier to support qualitative spatial relations in the pattern model. Finally, we propose a framework to manage spatiotemporal patterns in order to facilitate the integration of our pattern representation model to existing applications in the industry. The main contributions of this thesis are as follows: A qualitative approach to model dynamic spatiotemporal situations of interest using Conceptual Graphs. ; A cognitive approach to represent spatiotemporal patterns by integrating contextual information. ; An automated tool to generate qualitative spatial proximity relations based on a neuro-fuzzy classifier. ; A platform for detection and management of spatiotemporal patterns using an extension of a Complex Event Processing engine

The use of XML schema and XSLT rules for product information personalization

This thesis describes research carried out in order to help solve the problem of personalization in e-commerce/CRM system. Web-based personalization consists of activities, such as providing customised information, that tailor the user's Web experience- browsing a Web site or purchasing a product, for example-to that user's particular needs. The main research objective of the project is to investigate how XSLT technologies can be used for the development of matching engines that find XML represented products that match the tastes, needs or requirements of customers as captured in customer profiles, also represented in XML. More specifically our research investigates into novel algorithms for transforming XML based product specifications using rules that derive from mining customer profiles with the purpose of customizing the product information