104,958 research outputs found

    On the probabilistic logical modelling of quantum and geometrically-inspired IR

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    Information Retrieval approaches can mostly be classed into probabilistic, geometric or logic-based. Recently, a new unifying framework for IR has emerged that integrates a probabilistic description within a geometric framework, namely vectors in Hilbert spaces. The geometric model leads naturally to a predicate logic over linear subspaces, also known as quantum logic. In this paper we show the relation between this model and classic concepts such as the Generalised Vector Space Model, highlighting similarities and differences. We also show how some fundamental components of quantum-based IR can be modelled in a descriptive way using a well-established tool, i.e. Probabilistic Datalog

    A unified logical-linguistic indexing for search engines and question answering.

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    Conventional information representation models used in the search engines rely on an extensive use of keywords and their frequencies in storing and retrieving information. It is believed that such an approach has reached its upper limit of retrieval effectiveness, and therefore, new approaches should be investigated for the development of future engines which will be more effective. Logical-linguistic model is an alternative to conventional approach where logic and linguistic formalism are used in providing mechanism for computer to understand the contents of the source and deduce answers to questions. The capability of deduction is much depended on the knowledge representation framework used. We propose a unified logical-linguistic model as knowledge representation framework as a basis for indexing of documents as well as deduction capability to provide answers to queries. The approach applies semantic analysis in transforming and normalising information from natural language texts into a declarative knowledge based representation of first order predicate logic. Retrieval of relevant information can then be performed through plausible logical implication and answer to query is carried out using theorem proving technique. This paper elaborates on the model and how it is used in search engine and question answering system as one unified model

    Sustaining Collection Value: Managing Collection/Item Metadata Relationships

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    Many aspects of managing collection/item metadata relationships are critical to sustaining collection value over time. Metadata at the collection-level not only provides context for finding, understanding, and using the items in the collection, but is often essential to the particular research and scholarly activities the collection is designed to support. Contemporary retrieval systems, which search across collections, usually ignore collection level metadata. Alternative approaches, informed by collection-level information, will require an understanding of the various kinds of relationships that can obtain between collection-level and item-level metadata. This paper outlines the problem and describes a project that is developing a logic-based framework for classifying collection-level/item-level metadata relationships. This framework will support (i) metadata specification developers defining metadata elements, (ii) metadata librarians describing objects, and (iii) system designers implementing systems that help users take advantage of collection-level metadata.Institute for Museum and Libary Services (Grant #LG06070020)published or submitted for publicationis peer reviewe

    Passage retrieval in legal texts

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    [EN] Legal texts usually comprise many kinds of texts, such as contracts, patents and treaties. These texts usually include a huge quantity of unstructured information written in natural language. Thanks to automatic analysis and Information Retrieval (IR) techniques, it is possible to filter out information that is not relevant and, therefore, to reduce the amount of documents that users need to browse to find the information they are looking for. In this paper we adapted the JIRS passage retrieval system to work with three kinds of legal texts: treaties, patents and contracts, studying the issues related with the processing of this kind of information. In particular, we studied how a passage retrieval system might be linked up to automated analysis based on logic and algebraic programming for the detection of conflicts in contracts. In our set-up, a contract is translated into formal clauses, which are analysed by means of a model checking tool; then, the passage retrieval system is used to extract conflicting sentences from the original contract text. © 2011 Elsevier Inc. All rights reserved.We thank the MICINN (Plan I+D+i) TEXT-ENTERPRISE 2.0: (TIN2009-13391-C04-03) research project. The work of the second author has been possible thanks to a scholarship funded by Maat Gknowledge in the framework of the project with the Universidad Politécnica de Valencia Módulo de servicios semánticos de la plataforma GRosso, P.; Correa García, S.; Buscaldi, D. (2011). Passage retrieval in legal texts. Journal of Logic and Algebraic Programming. 80(3-5):139-153. doi:10.1016/j.jlap.2011.02.001S139153803-

    RAPID WEBGIS DEVELOPMENT FOR EMERGENCY MANAGEMENT

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    The use of spatial data during emergency response and management helps to make faster and better decisions. Moreover spatial data should be as much updated as possible and easy to access. To face the challenge of rapid and updated data sharing the most efficient solution is largely considered the use of internet where the field of web mapping is constantly evolving. ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action) is a non profit association founded by Politecnico di Torino and SITI (Higher Institute for the Environmental Systems) as a joint project with the WFP (World Food Programme). The collaboration with the WFP drives some projects related to Early Warning Systems (i.e. flood and drought monitoring) and Early Impact Systems (e.g. rapid mapping and assessment through remote sensing systems). The Web GIS team has built and is continuously improving a complex architecture based entirely on Open Source tools. This architecture is composed by three main areas: the database environment, the server side logic and the client side logic. Each of them is implemented respecting the MCV (Model Controller View) pattern which means the separation of the different logic layers (database interaction, business logic and presentation). The MCV architecture allows to easily and fast build a Web GIS application for data viewing and exploration. In case of emergency data publication can be performed almost immediately as soon as data production is completed. The server side system is based on Python language and Django web development framework, while the client side on OpenLayers, GeoExt and Ext.js that manage data retrieval and user interface. The MCV pattern applied to javascript allows to keep the interface generation and data retrieval logic separated from the general application configuration, thus the server side environment can take care of the generation of the configuration file. The web application building process is data driven and can be considered as a view of the current architecture composed by data and data interaction tools. Once completely automated, the Web GIS application building process can be performed directly by the final user, that can customize data layers and controls to interact with the

    Continuous Improvement Through Knowledge-Guided Analysis in Experience Feedback

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    Continuous improvement in industrial processes is increasingly a key element of competitiveness for industrial systems. The management of experience feedback in this framework is designed to build, analyze and facilitate the knowledge sharing among problem solving practitioners of an organization in order to improve processes and products achievement. During Problem Solving Processes, the intellectual investment of experts is often considerable and the opportunities for expert knowledge exploitation are numerous: decision making, problem solving under uncertainty, and expert configuration. In this paper, our contribution relates to the structuring of a cognitive experience feedback framework, which allows a flexible exploitation of expert knowledge during Problem Solving Processes and a reuse such collected experience. To that purpose, the proposed approach uses the general principles of root cause analysis for identifying the root causes of problems or events, the conceptual graphs formalism for the semantic conceptualization of the domain vocabulary and the Transferable Belief Model for the fusion of information from different sources. The underlying formal reasoning mechanisms (logic-based semantics) in conceptual graphs enable intelligent information retrieval for the effective exploitation of lessons learned from past projects. An example will illustrate the application of the proposed approach of experience feedback processes formalization in the transport industry sector
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