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 |
https://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 |