Please use this identifier to cite or link to this item:
http://dspace.unimap.edu.my:80/xmlui/handle/123456789/42029
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Roshidi, Yaakub | - |
dc.date.accessioned | 2016-06-12T10:44:46Z | - |
dc.date.available | 2016-06-12T10:44:46Z | - |
dc.date.issued | 2015-06 | - |
dc.identifier.uri | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/42029 | - |
dc.description | Access is limited to UniMAP community. | en_US |
dc.description.abstract | This project presents the classification of unknown words in English using Jaccard similarity based on the distributional of similar words. Information from FrameNet, a lexical database is utilized to determine the class of unknown words. The importance of unknown words classification is to recognize the meaning of unknown words in Natural Processing Language (NPL) systems. First, a program is designed to extract the words from a sequences of sentences which taken from news articles. Next, a program is designed a measure of Jaccard similarity with C programming language to compare words similarity between the words around unknown word which extracted from Document Understanding Conference (DUC) data and the words around the example sentences from FrameNet lexical database using Jaccard coefficient. The similarity measures the occurrence of words around the unknown word with all example sentences from FrameNet. Finally, the performance of this proposed similarity measurement method is evaluated by measuring the precision, recall, and f-measure of the unknown word identification. Furthermore, the test results presented the advantage and disadvantages of the proposed similarity measurement method that applied to classify the English unknown word based on the distributional of similar words. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Universiti Malaysia Perlis (UniMAP) | en_US |
dc.subject | FrameNet | en_US |
dc.subject | Classification of words | en_US |
dc.subject | Jaccard similarity | en_US |
dc.subject | Unknown words | en_US |
dc.subject | Language | en_US |
dc.title | Named entity recognition using framenet | en_US |
dc.type | Learning Object | en_US |
dc.contributor.advisor | Dr. Nik Adilah Hanin Zahri | en_US |
dc.publisher.department | School of Computer and Communication Engineering | en_US |
Appears in Collections: | School of Computer and Communication Engineering (FYP) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Abstract,Acknowledgement.pdf | 270.03 kB | Adobe PDF | View/Open | |
Introduction.pdf | 234.21 kB | Adobe PDF | View/Open | |
Literature Review.pdf | 260 kB | Adobe PDF | View/Open | |
Methodology.pdf | 360.45 kB | Adobe PDF | View/Open | |
Results and Discussion.pdf | 180.35 kB | Adobe PDF | View/Open | |
Conclusion and Recommendation.pdf | 101.33 kB | Adobe PDF | View/Open | |
Refference and Appendics.pdf | 194.85 kB | Adobe PDF | View/Open |
Items in UniMAP Library Digital Repository are protected by copyright, with all rights reserved, unless otherwise indicated.