A Multi-Relational Network to Support the Scholarly Communication Process

The general pupose of the scholarly communication process is to support the creation and dissemination of ideas within the scientific community. At a finer granularity, there exists multiple stages which, when confronted by a member of the community, have different requirements and therefore different solutions. In order to take a researcher's idea from an initial inspiration to a community resource, the scholarly communication infrastructure may be required to 1) provide a scientist initial seed ideas; 2) form a team of well suited collaborators; 3) located the most appropriate venue to publish the formalized idea; 4) determine the most appropriate peers to review the manuscript; and 5) disseminate the end product to the most interested members of the community. Through the various delinieations of this process, the requirements of each stage are tied soley to the multi-functional resources of the community: its researchers, its journals, and its manuscritps. It is within the collection of these resources and their inherent relationships that the solutions to scholarly communication are to be found. This paper describes an associative network composed of multiple scholarly artifacts that can be used as a medium for supporting the scholarly communication process.Comment: keywords: digital libraries and scholarly communicatio

Exposing Multi-Relational Networks to Single-Relational Network Analysis Algorithms

Many, if not most network analysis algorithms have been designed specifically for single-relational networks; that is, networks in which all edges are of the same type. For example, edges may either represent "friendship," "kinship," or "collaboration," but not all of them together. In contrast, a multi-relational network is a network with a heterogeneous set of edge labels which can represent relationships of various types in a single data structure. While multi-relational networks are more expressive in terms of the variety of relationships they can capture, there is a need for a general framework for transferring the many single-relational network analysis algorithms to the multi-relational domain. It is not sufficient to execute a single-relational network analysis algorithm on a multi-relational network by simply ignoring edge labels. This article presents an algebra for mapping multi-relational networks to single-relational networks, thereby exposing them to single-relational network analysis algorithms.Comment: ISSN:1751-157

Maintaining computer-based information systems using text-based intelligent systems techniques

In order to incorporate up-to-date quantitative and qualitative information, Computer- Based Information Systems (CBIS) must be able to extract data from unstructured, textual formats such as newspapers and magazines. The process of updating information in a CBIS currently requires large amounts of human effort analyzing and converting data from such sources into formats which information systems can work with. This paper suggests some methods by which the data needs of a CBIS can be handled semi-automatically (Employing both computers and humans) using text-based intelligent systems (TBIS) techniques

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

RELIEFS : un système d'inspiration cognitive pour le filtrage adaptatif de documents textuels

International audienceL'objet de cet article est la présentation d'un nouveau système nommé RELIEFS (pour RELevance Information Extraction Fuzzy System) pour le filtrage adaptatif de documents textuels. Les grands principes de fonctionnement de ce système s'inspirent de mécanismes cognitifs intervenant dans les processus de sélection de l'information. Plus précisément, notre recherche part de l'analyse de modèles de la mémoire sémantique (accès et organisation des connaissances en mémoire) et de modèles qui rendent compte de phénomènes attentionnels (sélection des informations provenant de l'environnement). Des liens forts sont tissés entre ces modèles et des modèles traditionnellement utilisés en RI. Une nouvelle interprétation de la notion de pertinence est proposée. L'analyse nous conduit à extraire un ensemble de mécanismes de base renvoyant aux notions d'activation et de propagation d'activation pour la sélection d'information " pertinentes ". Ces mécanismes sont implémentés et testés avec succès dans la tâche de filtrage adaptatif de TREC9

Towards the use of situational information in information retrieval

This paper is an exploratory study of one approach to incorporating situational information into information retrieval systems, drawing on principles and methods of discourse linguistics. A tenet of discourse linguistics is that texts of a specific type possess a structure above the syntactic level, which follows conventions known to the people using such texts to communicate. In some cases, such as literature describing work done, the structure is closely related to situations, and may therefore be a useful representational vehicle for the present purpose. Abstracts of empirical research papers exhibit a well-defined discourse- level structure, which is revealed by lexical clues. Two methods of detecting the structure automatically are presented: (i) a Bayesian probabilistic analysis; and (ii) a neural network model. Both methods show promise in preliminary implementations. A study of users\u27 oral problem statements indicates that they are not amenable to the same kind of processing. However, from in-depth interviews with users and search intermediaries, the following conclusions are drawn: (i) the notion of a generic research script is meaningful to both users and intermediaries as a high-level description of situation; (ii) a researcher\u27s position in the script is a predictor of the relevance of documents; and (iii) currently, intermediaries can make very little use of situational information. The implications of these findings for system design are discussed, and a system structure presented to serve as a framework for future experimental work on the factors identified in this paper. The design calls for a dialogue with the user on his or her position in a research script and incorporates features permitting discourse-level components of abstracts to be specified in search strategies

Hytexpros : a hypermedia information retrieval system

The Hypermedia information retrieval system makes use of the specific capabilities of hypermedia systems with information retrieval operations and provides new kind of information management tools. It combines both hypermedia and information retrieval to offer end-users the possibility of navigating, browsing and searching a large collection of documents to satisfy an information need. TEXPROS is an intelligent document processing and retrieval system that supports storing, extracting, classifying, categorizing, retrieval and browsing enterprise information. TEXPROS is a perfect application to apply hypermedia information retrieval techniques. In this dissertation, we extend TEXPROS to a hypermedia information retrieval system called HyTEXPROS with hypertext functionalities, such as node, typed and weighted links, anchors, guided-tours, network overview, bookmarks, annotations and comments, and external linkbase. It describes the whole information base including the metadata and the original documents as network nodes connected by links. Through hypertext functionalities, a user can construct dynamically an information path by browsing through pieces of the information base. By adding hypertext functionalities to TEXPROS, HyTEXPROS is created. It changes its working domain from a personal document process domain to a personal library domain accompanied with citation techniques to process original documents. A four-level conceptual architecture is presented as the system architecture of HyTEXPROS. Such architecture is also referred to as the reference model of HyTEXPROS. Detailed description of HyTEXPROS, using the First Order Logic Calculus, is also proposed. An early version of a prototype is briefly described