Investigating the combination of structural and textual information about multimedia retrieval
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The expansion of structured information in different applications introduces a new ambiguity in multimedia retrieval in semi-structured documents. We investigate in this paper the combination of textual and structural context for multimedia retrieval in XML document thus we present a indexing model which combines textual and structural information. We propose a geometric method who use implicitly of textual and structural context of XML elements and we are particularly interested by improve the effectiveness of various structural factors for multimedia retrieval. Using a geometric metric, we can represent structural information in XML document with a vector for each element. Given a textual query, our model lets us combine scores obtained from each sources of evidence and return a list of relevant retrieved multimedia element. Experimental evaluation is carried out using the INEX Ad Hoc Task 2007 and the Image CLEF Wikipedia Retrieval Task 2010. The results show that combination of scores of textual modality and structural modality significantly improves compared results of using a single modality.Keywords:
Modality (human–computer interaction)
The objective of NLM's Indexing Initiative (IND) is to investigate methods whereby automated indexing methods partially or completely substitute for current indexing practices. The project will be considered a success if methods can be designed and implemented that result in retrieval performance that is equal to or better than the retrieval performance of systems based principally on humanly assigned index terms. We describe the current state of the project and discuss our plans for the future.
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To implement the indexing in multilingual dataset, the indexing process must know. This paper gives the brief about indexing and presents role of indexing, logical view of indexing, types of indexing, indexing process, data structure of indexing, representation of indexing and indexing framework. Indexing is an important concept to implement in retrieval process. By the indexing, retrieval process will reduce the time. The indexing part performs the complete article pool to shape index constructions that permit for resourceful search. These are typically inverted tables. Each article is so preprocessed and recorded to a vector demonstration. At the end indexing method is applied to the multilingual information retrieval system and shows the results.
Vector space model
Automatic indexing
Representation
Adversarial information retrieval
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There are many problems existing in CLC,such as paying no attention to indexing,indexing only in accorduce with titles,indexing but not comprehensive,etc.In CLC indexing the following principles should be observed:the principles of accuracy and comprehensiveness,the principle of paying particular attention and the principle of classification.At the same time,the author poses that the editors in the indexing CLC should strengthen the sense of responsibility for right indexing to achieve indexing CLC purposes.
Automatic indexing
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Spatial indexing cam is widely used in some automation machineries, and usually can be classified into the following three types: (1) cylindrical indexing cam; (2) parallel indexing cam; (3) globular indexing cam. These cams have their own use range, and also are different in index number and application accuracy. In this paper, cylindrical indexing cam is mainly analyzed.
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Automatic indexing
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In this paper ,modality construed as a pragmatic notion, is classified into two categories with respect to markedness: unmarked modality and marked modality. The latter is further divided into strong modality,neutral modality and weak modality. Based on this classification, a variety of marked expressions indicating modality are examined. In conclusion, this essay argues that there are still many problems with the conventional classification of modality, which requires re-examination
Modality (human–computer interaction)
Markedness
Treatment modality
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Traditional indexing techniques are not well suited for complex data types such as spatial, spatio-temporal, and multimedia data types, where an instance is a composite of multiple components. In this paper we propose two indexing techniques that allow the parts of a composite object to be indexed separately, called multiple entry indexing and double indexing. We present the implementation of these approaches in the SECONDO extensible database system. The improvements in terms of performance of both approaches presented in this paper are shown in an experimental evaluation.
Database index
Extensibility
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In submitting articles to some journals and bulletins, authors are responsible for indexing their own works. Indexing consists of identifying concepts and translating those concepts into indexing terms appropriate to the discipline and to indexing constraints. The constraints help an author/indexer decide how to determine the number and specificity of terms. In some systems indexing vocabulary is controlled by a thesaurus, which helps in selecting terms and considering alternatives. Authors as indexers should pursue the goal of all indexing — to match indexing assignments to the terms most likely to be chosen by prospective readers.
Automatic indexing
Controlled vocabulary
Thesaurus
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This paper gives an in-depth knowledge about indexing and indexing parameters. A study of indexing and detailed calculations of indexing parameters like Impact Factor, Site score, h-index, m-index, g-index are really helpful to the new-comers in the area of research. The paper suggests some steps to get a journal to be indexed. The paper would try to have a closer look on indexing and indexing parameters.
Automatic indexing
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