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Document indexation is an essential task achieved by archivists or automatic indexing tools. To retrieve relevant documents to a query, keywords describing this document have to be carefully chosen. Archivists have to find out the right topic of a document before starting to extract the keywords. For an archivist
Image annotation becomes increasingly more important as the Web continues to grow. We propose a novel approach to enhancing keyword-based Web-image annotation in folksonomy, where a volunteer user is notified what kind(s) of keywords are necessary, and that keywords have been sufficiently provided by other volunteer
In the information retrieval process, the selection of keywords and the generation of queries are very critical for the efficient retrieval. However, users experience the difficulties of selecting major keywords without being aware of the domain context. This paper proposes an automatic query generation method using n
suggest the ways that make and renew the ontology, which are related with the keywords that users input in the search engine, automatically for the automatic generation of ontology that is not limited by specific domain. Input keyword and relation keywords become OWL, and the relation among the created OWL is expressed by
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
Due to the huge number of research articles in the biomedical domain, it becomes more and more important to develop methods to find relevant articles of our specific research interests. Keyword extraction is a useful method to find important topics from documents and summarize their major information. Unfortunately
keyword search, meaning that the user needs to know the correct keywords before being able to retrieve the content of Quran. In this paper, we propose a system that supports the end user in querying and exploring the Quran ontology. The system comprises user query reformulation against the Quran ontology stored and annotated
conceptual model is well defined, a set of rules for keyword searching is created to verify preciseness of output produced. The rules created in this paper will be executed on Herbal Research E-Centre prototype.
The Holy Quran, due to its unique style and allegorical nature, needs special attention about searching and information retrieval issues. The legacy keyword searching techniques are incapable of retrieving semantically relevant verses. In this paper, we address the deficiencies of key word based searching and the
Metacat to improve metadata search in multiple ways: (i) by expanding standard keyword searches with ontology term hierarchies; (ii) by allowing keyword searches to be applied to annotations in addition to traditional meta-data; and (iii) by allowing more structured searches over annotations via ontology terms. We describe
avoid unnecessary email reading for that a better email management system is required. Here author used fuzzy logic techniques for email clustering. Extract concept and feature, same feature keyword goes into one cluster if a new keyword is found and not matched with any existing cluster than a new cluster is defined for
and completeness through sense disambiguation and contextual meta-data prepossessing. Our schemes exploits a linguistic ontology identifying query relevant homographs used to construct sense specific keyword sets allowing for enhanced image search and result ranking via the calculation of relatedness between query
The development and maintenance of domain knowledge based system need a lot of manual operations, and with the increasing amount of contents in the system, it is more and more difficult to find the relevant information. The keyword based search usually can not return the accurate result. To solve these problems, this
Current keyword search by Google, Yahoo, and so on gives enormous unsuitable results. A solution to this perhaps is to annotate semantics to textual web data to enable semantic search, rather than keyword search. However, pure manual annotation is very time-consuming. Further, searching high level concept such as
needed to search and find relevant information. For tabular structures embedded in HTML documents, typical keyword or link-analysis based search fails. The next phase envisioned for the WWW is automatic ad-hoc interaction between intelligent agents, web services, databases and semantic web enabled applications. A large
This system proposes Indian-logic ontology based Context-aware Query Refinement model to support context-sensitive semantic search in keyword based search engine. This is by formulating effective query using Indian logic based Ontology for Context identification to overcome ambiguous query terms and increase the
This paper presents an overview of the emerging field of emotion detection from text and describes the current generation of detection methods that are usually divided into the following three main categories: keyword-based, learning-based, and hybrid recommendation approaches. Limitations of current detection methods
Assigning keywords to articles can be extremely costly. In this paper we propose a new approach to biomedical concept extraction using semantic features of concept graphs to help in automatic labeling of scientific publications. The proposed system extracts key concepts similar to author-provided keywords. We
In this paper, we present an ontology-based information extraction and retrieval system and its application to soccer domain. In general, we deal with three issues in semantic search, namely, usability, scalability and retrieval performance. We propose a keyword-based semantic retrieval approach. The performance of
form of an ontology which represents the distinct areas of Software Engineering knowledge inspired by SWEBOK (Software Engineering Body of Knowledge). Finally, the process of the classification of texts within the ontology is carried out in three steps: keyword analysis, processing of the document. We believe our proposal
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