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Efficient Indexing and Searching Framework for Unstructured Data

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dc.contributor.author Aye, Kyar Nyo
dc.contributor.author Thein, Ni Lar
dc.date.accessioned 2019-07-16T05:59:32Z
dc.date.available 2019-07-16T05:59:32Z
dc.date.issued 2011-12-10
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/912
dc.description.abstract The proliferation of unstructured data continues to grow within organizations of all types. This data growth has introduced the key question of how we effectively find and manage them in the growing sea of information. As a result, there has been an increasing demand for efficient search on them. Providing effective indexing and search on unstructured data is not a simple task. Unstructured data include documents, images, audio, video and so on. In this paper, we propose an efficient indexing and searching framework for unstructured data. In this framework, text-based and content-based approaches are incorporated for unstructured data retrieval. Our retrieval framework can support various types of queries and can accept multimedia examples and metadata-based documents. The aim of this paper is to use various features of multimedia data and to make content-based multimedia retrieval system more efficient. en_US
dc.language.iso en en_US
dc.publisher International Conference on Software and Computing Technology (ICSCT), Singapore en_US
dc.relation.ispartofseries SPIE;Vol.8349
dc.subject unstructured data en_US
dc.subject indexing en_US
dc.subject content-based retrieval en_US
dc.title Efficient Indexing and Searching Framework for Unstructured Data en_US
dc.type Article en_US


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