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The traditional layout of news websites, the combination of classified hierarchical browsing, headline recommendation and keyword-based search, has been used for many years. The keyword-based search is considered to be the most powerful tool for news browsing and retrieval. Unfortunately, the keyword-based query
The semantic search promises to provide more accurate results than the current keyword matching-based search by understanding user intent and the contextual meaning of terms based on knowledge base. However, the ordinary users have difficulty in using the complex formal query language and the knowledge base schema on
may not be suitable for educational purposes. Also, finding pedagogic illustrations still requires manual work, which is difficult and time-consuming. The commonly used systems based on the best keyword selection and the best sentence selection may suffer from loss of information. In this paper, we present an Arabic
Semantic search promises to provide more accurate result than present-day keyword matching-based search by using the knowledge represented logically (i.e., knowledge base). But, the ordinary users don't know well the complex formal query language and schema of the knowledge base. So, the system should interpret the
tell the same story, share the same space-time extension, and they might be closely related to each other. Previous efforts in information retrieval and integration have been limited to classical keyword-based and content-based indexing and querying for multiple media documents. Furthermore, the concept-based approach
search techniques. In this paper, we introduce an associated semantic network as the semantic representation model; use semantic keywords, a linguistic ontology in semantic similarity calculation and use learner relevance feedback to complete automatic semantic annotation. After several iterations of learner relevance
comprises of several components; (1) using a Stemming algorithm for text processing, (2) Formal Concept Analysis for dynamic extraction of keywords, (3) Ontology based concept extraction, (4)Google API is used to query the Google Image Database and extract the required multimedia elements, which are then mapped accordingly. A
The Imagelab Laboratory of the University of Modena and Reggio Emilia has designed a large video repository, aiming at containing annotated video surveillance footages. The Web interface, named ViSOR (video surveillance online repository), allows video browse, query by annotated concepts or by keywords, compressed
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.