Abstract
Natural language query systems mitigate the complexity of structured query. Usually, natural language processing is implemented to solve several problems, such as information retrieval. However, problems such as natural language ambiguity remain unsolved due to the complexity of natural language itself. This issue thus requires further research. Recent studies on semantic query formulation have attempted to resolve ambiguous natural language by proposing different disambiguation approaches. Most such processes are either implemented manually or semi-automated. In the same vein, most recent systems solve ambiguity by using an external dictionary such as WordNet or by providing suggestions manually. The present research proposes a statistical linguistic technique for solving the problem of ambiguity automatically. The proposed technique is experimentally tested on a Quran ontology with queries from the Islamic Research Foundation Website and increases the result of precision and recall by 6% and 10%, respectively.
| Original language | English |
|---|---|
| Pages (from-to) | 48-56 |
| Number of pages | 9 |
| Journal | Malaysian Journal of Computer Science |
| Volume | 31 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 1 Jan 2018 |
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Keywords
- Information retrieval
- Islamic knowledge
- Ontology
- Semantic technology
- Statistical linguistics technique
ASJC Scopus subject areas
- Computer Science(all)
Cite this
Semantic ambiguous query formulation using statistical Linguistics technique. / Rabiah, Abdul Kadir; Yauri, Rufai Aliyu; Azman, Azreen.
In: Malaysian Journal of Computer Science, Vol. 31, No. 5, 01.01.2018, p. 48-56.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Semantic ambiguous query formulation using statistical Linguistics technique
AU - Rabiah, Abdul Kadir
AU - Yauri, Rufai Aliyu
AU - Azman, Azreen
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Natural language query systems mitigate the complexity of structured query. Usually, natural language processing is implemented to solve several problems, such as information retrieval. However, problems such as natural language ambiguity remain unsolved due to the complexity of natural language itself. This issue thus requires further research. Recent studies on semantic query formulation have attempted to resolve ambiguous natural language by proposing different disambiguation approaches. Most such processes are either implemented manually or semi-automated. In the same vein, most recent systems solve ambiguity by using an external dictionary such as WordNet or by providing suggestions manually. The present research proposes a statistical linguistic technique for solving the problem of ambiguity automatically. The proposed technique is experimentally tested on a Quran ontology with queries from the Islamic Research Foundation Website and increases the result of precision and recall by 6% and 10%, respectively.
AB - Natural language query systems mitigate the complexity of structured query. Usually, natural language processing is implemented to solve several problems, such as information retrieval. However, problems such as natural language ambiguity remain unsolved due to the complexity of natural language itself. This issue thus requires further research. Recent studies on semantic query formulation have attempted to resolve ambiguous natural language by proposing different disambiguation approaches. Most such processes are either implemented manually or semi-automated. In the same vein, most recent systems solve ambiguity by using an external dictionary such as WordNet or by providing suggestions manually. The present research proposes a statistical linguistic technique for solving the problem of ambiguity automatically. The proposed technique is experimentally tested on a Quran ontology with queries from the Islamic Research Foundation Website and increases the result of precision and recall by 6% and 10%, respectively.
KW - Information retrieval
KW - Islamic knowledge
KW - Ontology
KW - Semantic technology
KW - Statistical linguistics technique
UR - http://www.scopus.com/inward/record.url?scp=85065479288&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85065479288&partnerID=8YFLogxK
U2 - 10.22452/mjcs.sp2018no1.4
DO - 10.22452/mjcs.sp2018no1.4
M3 - Article
AN - SCOPUS:85065479288
VL - 31
SP - 48
EP - 56
JO - Malaysian Journal of Computer Science
JF - Malaysian Journal of Computer Science
SN - 0127-9084
IS - 5
ER -