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Searching is a necessary tool for managing and navigating the massive amounts of data available in today's information age. While new searching methods have become increasingly popular and reliable in recent years, such as image-based searching, these methods may be more limited than text-based means in that they do not allow generic user input. Sketch-based searching is a method that allows users...
In recent years, the fast growth of Web pages and the constant evolution of internet technologies have lead to a significant increase in the number of pedagogical resources. Thus, the indexing and search problems have become crucial. To overcome this problem, it was proposed to use information coming from the norms and standards of educational metadata. However, this solution does not solve completely...
In this paper, we present a statistical approach to semantic indexing for multilingual text documents based on conceptual network formalism. We propose to use this formalism as an indexing language to represent the descriptive concepts and their weighting. These concepts represent the content of the document. Our contribution is based on two steps; we propose, in the first step, the extraction of...
There is an emerging international phenomenon of drugs that are sold without any control on online marketplaces. An example of a former online marketplace is Silk Road, best known as a platform for selling illegal drugs operated as a Tor hidden service. Silk Road was closed by FBI in 2013 but new alternatives have appeared since illicit substances is a big market. One problem with online marketplaces...
This paper describes a method for querying lifelog data from visual content and from metadata associated with the recorded images. Our approach mainly relies on mapping the query terms to visual concepts computed on the Lifelogs images according to two separated learning schemes based on use of deep visual features. A post-processing is then performed if the topic is related to time, location or activity...
The user's location is an important information to describe the current situation or context. In some scenarios, we have to rely on a purely textual description when a digital map is not available. Our approach efficiently generates a meaningful text that describes the current location. As an appropriate text is highly application-dependent, a formalism supports applications to configure the desired...
The automated indexing of image and video is a difficult problem because of the “distance” between the arrays of numbers encoding these documents and the concepts (e.g. people, places, events or objects) with which we wish to annotate them. Methods exist for this but their results are far from satisfactory in terms of generality and accuracy. Existing methods typically use a single set of such examples...
We revisit text-based image retrieval for social media, exploring the opportunities offered by statistical semantics. We assess the performance and limitation of several complementary corpus-based semantic text similarity methods in combination with word representations. We compare results with state-of-the-art text search engines. Our deep learning-based semantic retrieval methods show a statistically...
The information world WWW has more than 3 billion HTML pages and these web pages gain access through search engines only. Search engine is a program that searches the document for specified set of keywords and returns a list of documents where any or all of the specified keywords were found. As more information becomes available on the web, it is more difficult to provide effective search services...
Retrieval engines provide results according to user request. Nevertheless, reaching satisfaction can not be guaranteed with simple retrieval step. Therefore, it is necessary to communicate this dissatisfaction to the system through relevance feedback techniques. Indeed, with the growing number of image collections and by applying approximate nearest neighbor (ANN) algorithms to resolve the curse of...
Digital libraries on distance learning platforms are ways that allow learners to consult and enrich their knowledge on the content that are studied in their course. In this paper, we are interested in the semantic analysis of the content of the resources visited in the digital libraries (eBooks) by learners using domain ontology. The purpose of this analysis is to identify the domain concepts that...
As opposed to query reformulation oriented towards changes made by a user to specify the information need more precisely, a post-search query modeling is a technique of exploiting syntax variation of gradually extended query which depending on some other factors like e.g. the resource, database or the key word alignment, facilitates the searching process. The study into modeling query submitted to...
With the growing needs of dimension reduction for term selection and recommendation and the up to date trends in natural language processing modules integrated in existing architectures and multiple semantic web system such as search engine. The existence of multiples tokenization techniques of the same text represents a persistent problem in current semantic search engine practice and create a non-trivial...
Human action video retrieval is a useful tool for video surveillance and sports video analysis, among other applications. Previous work on image retrieval tasks has shown that latent semantic methods are an effective way to build a high-level representation of data to discover implicit relations between visual patterns, achieving a significant improvement on these tasks. The current paper evaluates...
Information Technology brought many applications of Information Retrieval as simple as possible through Web and other Digital Information Access Environment. There is a demand in building Applications of IR in Local languages, which allows common people with minimal knowledge in at least one language to avail the information services. Word mismatch is a common problem in IR System Applications. The...
Classical IR systems are often based on lexical matching using approaches that rely on purely statistical methods founded on distributions of keywords to calculate the similarity between the query and the documents of the corpus. The relevance of a document according to a query is based on the similarity of vocabulary and not according to the thematic similarity between both. Indeed, a document selected...
The goal of the research described here is to present an approach for automating the detection and the extraction of meaning from text using a range of linguistic and ontological techniques, concepts such as the lexico-semantic functions proposed in Meaning-Text Theory by Mel'cuk and the concept of the context. This is motivated, by the fact that, on one hand, these functions enable a better modeling...
In an effort to develop effective multi-media learning objects (MLO), we propose a framework to extract and associate semantic tags to temporally segmented instructional videos. These tags serve for the purpose of efficient indexing and retrieval system. We create these semantic tags from potential keywords extracted from the lecture transcript. The keywords undergo a series of refinement process...
Information research refers, in our context, to information retrieval to obtain further learning information from documents. However, automatic tools for learning information retrieval from these documents based on semantic tags are not yet effective. We propose here a model which aims at automatically annotating texts with semantic metadata. These metadata will allow us to index and extract learning...
Web services offer a vast number of interoperable programs. The problem of web services is how to develop mechanisms to locate automatically the correct Web service in order to meet the user's requirements, that is appointed by the discovery of web services. Indeed, it is beyond the human's capability to manually analyse web services functionalities. This paper proposes an architectural model to assist...
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