خلاصة:
Extension of information together with the need for its use ine and appropriate time is one of the important goals in this century - the information century. The user query that is accessibility to the requested text information in a short time must be satisfied using eftéctive techniques. This is performable under text compression and retrieval. which have been treated separately before. In this paper an algorithm, that considers the above two subjects as integrated (text integration), is introduced and implemented. From this point of view, the possibility of text optimization from two aspects can be applied. This article concentrates mainly on Farsi''’ texts.
ملخص الجهاز:
July/December, 2005 Iranian Journal of Information Science & Technology, Volume 3, Number 2 As discvisscd before, this papcr’s objcctive is to present a method by which text integration (compression along with eficctive acccss) can undergo user's needs oI‘fast rctriex'al tt›hethcr wilh less storage space consumption (optimization).
The uscr’s query for intormalion rctrieval may contain dittcrent goals thal arc suminarizcd as follows: Th is article tries to present an algorithm and/ter compression system to unclergo cases(c) and spccitically (d) of thc above, in of her words, to present an integrated system which has the two characteristics tif text rctrieval systems s imultancously.
Their great achievement is the development of a system which, based on Huffman coding, compresses a text using on word list for indexing and compression [5].
We now explain what mentioned above in more details: - I NDEXING & SEA RCHING We use indexing to find user's query-based texts more rapidly in an Information Retrieval (IR) system.
e. , codes are read from the compressed file, the corresponding word is figured out in the lexicon, and finally retrieved 4uly/December, 2005 Iranian Journal of Information Science & Technology, Volume 3, Number 2 iu a new file.
As we arc intended to retrieve those texts including a specify pattern, we necd tti locate and store all text words in oui index.
Table 2: Making lexicon word, code, 1 location, 1 frequency, 1 Then the main file needs to be compressed.
O Using integrated word list (lexicon) for indexing and compression.