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The evolution of information retrieval is intimately linked to the evolution of the Web. Although the involvement of different context dimensions in the improvement of the search task was greatly studied, the abundant development of hardware and software opens ways to explore new contextual dimensions. This paper presents the different contextual dimensions studies in the literature and proposes a...
Modern society is characterized by abundance of data, yet lack of (relevant) information. A major challenge consists in selecting valuable information according to specific criteria. Moreover, ranking it and defining relevance according to the context is decisive. We propose a framework to retrieve content according to context. Our approach relies on a three layers model, each contributing to a better...
Query difficulty prediction aims to identify, in advance, how reliably an information retrieval system will perform when faced with a particular user request. The prediction of query difficulty level is an interesting and important issue in Information Retrieval (IR) and is still an open research. In order to appreciate importance of query difficulty prediction we present an example., Information...
This paper reports a novel semantic web application developed to deliver a collaborative tagging system for a digital on-line museum. The key features of our application - called the Virtual Museum of the Pacific - concern the browsing and retrieval interface based on Formal Concept Analysis the extensible distributed data model to support collaborative tagging and its web services implementation.
Faceted Taxonomies are often used for managing complex knowledge within a domain. They can be used as a reference model for bottom-up new information analysis and integration. This paper proposes a domain information model that quantifies the semantics (indexing concepts) of the faceted taxonomy nodes and uses them as indexer for integrating and managing knowledge such as software requirements. Through...
Many approaches of terminology extraction make use of contextual information to acquire relations between terms. The quality and the quantity of this information influence the accuracy of the terminology extractor. In this paper, we assume that logical structure of documents constitute a rich source of contextual information which can be used to infer semantic relations between terms and thus construct...
Tagging-based systems are becoming a widely used tool as they are considered simple and quick to categorize resources. However, due to the free vocabulary used for tagging, and also because of its plane structure, there are some drawbacks inherent to this kind of system, mainly when users do the information retrieval. This paper presents a proposal for the emergence of ontologies from tagging-based...
For question answering, the multi-source approach is justifiable especially when different sources provide different types of knowledge. In this paper, a variety of question and answer types are revealed. The key point this paper addresses under the framework of extensible QA is efficient and consonant usage of a number of distinct QA techniques for improving the answer confidence. To prove the extensibility...
With the explosive growth of the information and services deployed to the Web, there is a pressing need to develop an effective service for personalized services discovery and recommendation. Despite personalized services discovery methods have been studied by researchers before, few attempts have been made to explore ontological user profiling and probabilistic language modeling approach for service...
Online support centers are emerging as a cost-effective and innovative solution designed to enable end-users to resolve technical problems more effectively without relying on live support from contact center agents. However, the capacity limitation of corporate knowledge bases prevents online support centers from effectively resolving user problems. In addition, traditional textual search techniques...
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