Change search
ReferencesLink to record
Permanent link

Direct link
Increasing usability using semantic analysis
2007 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

In linguistics, semantic analysis is a part of the Artificial Intelligence and it is a major interest in today’s research in Computer Science. Semantic analysis is using to study the meaning of words and fixed word combinations, and how these combine to form the meanings of sentences. When the users enter a input text to search a particual thing, the semantic analysis technique is using to finding out the matching content from the web text. For the users as well as for the application, semantic analysis is incresing the usability. To achiving this usability and incresing the facilities for the users, semantic anlysis is developing day by day. Like the human, the machine can also understand the human language now a days. So the machine is using for find out certine input texts or document from the online newspapers and web content texts. It is faster then human to collecting thousands and millions news in a certain amount of time. Some few techniques are developed to understand the text or document like crime report analysis and resume type recognization. Crime report analysis can find out the date, place and time of the crime. Which is easier to analysis by using the machine. But this system will not work for other different type of texts. So if we want to find out the object name, location, person name from a input text, there are no suitable technique for us. This thesis propose and describe a solution in the area of semantic analysis which will identify the object name, text type and priority from a users input text.

Place, publisher, year, edition, pages
Keyword [en]
Keyword [sv]
URN: urn:nbn:se:ltu:diva-42541ISRN: LTU-EX--07/167--SELocal ID: 08abb0c8-cce9-434a-a0e0-ef29b16ae22fOAI: diva2:1015764
Subject / course
Student thesis, at least 30 credits
Educational program
Computer Science and Engineering, master's level
Validerat; 20101217 (root)Available from: 2016-10-04 Created: 2016-10-04Bibliographically approved

Open Access in DiVA

fulltext(987 kB)0 downloads
File information
File name FULLTEXT01.pdfFile size 987 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

ReferencesLink to record
Permanent link

Direct link