14,936 research outputs found

    Improving Knowledge Retrieval in Digital Libraries Applying Intelligent Techniques

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    Nowadays an enormous quantity of heterogeneous and distributed information is stored in the digital University. Exploring online collections to find knowledge relevant to a user’s interests is a challenging work. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. In this work we propose a comprehensive approach for discovering E-learning objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We have used Case Based-Reasoning methodology to develop a prototype for supporting efficient retrieval knowledge from online repositories. We suggest a conceptual architecture for a semantic search engine. OntoUS is a collaborative effort that proposes a new form of interaction between users and digital libraries, where the latter are adapted to users and their surroundings

    NLSC: Unrestricted Natural Language-based Service Composition through Sentence Embeddings

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    Current approaches for service composition (assemblies of atomic services) require developers to use: (a) domain-specific semantics to formalize services that restrict the vocabulary for their descriptions, and (b) translation mechanisms for service retrieval to convert unstructured user requests to strongly-typed semantic representations. In our work, we argue that effort to developing service descriptions, request translations, and matching mechanisms could be reduced using unrestricted natural language; allowing both: (1) end-users to intuitively express their needs using natural language, and (2) service developers to develop services without relying on syntactic/semantic description languages. Although there are some natural language-based service composition approaches, they restrict service retrieval to syntactic/semantic matching. With recent developments in Machine learning and Natural Language Processing, we motivate the use of Sentence Embeddings by leveraging richer semantic representations of sentences for service description, matching and retrieval. Experimental results show that service composition development effort may be reduced by more than 44\% while keeping a high precision/recall when matching high-level user requests with low-level service method invocations.Comment: This paper will appear on SCC'19 (IEEE International Conference on Services Computing) on July 1

    Assessing Web Services Interfaces with Lightweight Semantic Basis

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    In the last years, Web Services have become the technological choice to materialize the Service-Oriented Computing paradigm. However, a broad use of Web Services requires efficient approaches to allow service consumption from within applications. Currently, developers are compelled to search for suitable services mainly by manually exploring Web catalogs, which usually show poorly relevant information, than to provide the adequate "glue-code" for their assembly. This implies a large effort into discovering, selecting and adapting services. To overcome these challenges, this paper presents a novel Web Service Selection Method. We have defined an Interface Compatibility procedure to assess structural-semantic aspects from functional specifications - in the form of WSDL documents - of candidate Web Services. Two different semantic basis have been used to define and implement the approach: WordNet, a widely known lexical dictionary of the English language; and DISCO, a database which indexes co-occurrences of terms in very large text collections. We performed a set of experiments to evaluate the approach regarding the underlying semantic basis and against third-party approaches with a data-set of real-life Web Services. Promising results have been obtained in terms of well-known metrics of the Information Retrieval field

    The Knowledge Life Cycle for e-learning

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    In this paper, we examine the semantic aspects of e-learning from both pedagogical and technological points of view. We suggest that if semantics are to fulfil their potential in the learning domain then a paradigm shift in perspective is necessary, from information-based content delivery to knowledge-based collaborative learning services. We propose a semantics driven Knowledge Life Cycle that characterises the key phases in managing semantics and knowledge, show how this can be applied to the learning domain and demonstrate the value of semantics via an example of knowledge reuse in learning assessment management
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