Answer Extraction System Based on Latent Dirichlet Allocation
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 4
Abstract
Question Answering (QA) task is still an active area of research in information retrieval. A variety of methods which have been proposed in the literature during the last few decades to solve this task have achieved mixed success. However, such methods developed in the Arabic language are scarce and do not have a good performance record. This is due to the challenges of Arabic language. QA based on Frequently Asked Questions is an important branch of QA in which a question is answered based on pre-answered ones. In this paper, the aim is to build a question answering system that responds to a user inquiry based on pre-answered questions. The proposed approach is based on Latent Dirichlet Allocation. Firstly, the dataset, pairs of questions and associated answers, will be grouped into several clusters of related documents. Next, when a new question to be answered is posed to the system, it,therefore, starts to assign this question to its appropriate cluster, then, use a similarity measure to get the top ten closest possible answers. Preliminary results show that the proposed method is achieving a good level of performance.
Authors and Affiliations
Mohammed Ali, Sherif Abdou
Keywords
Related Articles
- EP ID EP101486
- DOI 10.14569/IJACSA.2016.070461
- Views 106
- Downloads 0
Using Fuzzy Clustering Powered by Weighted Feature Matrix to Establish Hidden Semantics in Web Documents
Digital Data is growing exponentially exploding on the 'World Wide Web'. The orthodox clustering algorithms obligate various challenges to tackle, of which the most often faced challenge is the uncertainty. Web documents...
Local Average of Nearest Neighbors: Univariate Time Series Imputation
The imputation of time series is one of the most important tasks in the homogenization process, the quality and precision of this process will directly influence the accuracy of the time series predictions. This paper pr...
Competitive Sparse Representation Classification for Face Recognition
A method, named competitive sparse representation classification (CSRC), is proposed for face recognition in this paper. CSRC introduces a lowest competitive deletion mechanism which removes the lowest competitive sample...
Measuring the Effect of Packet Corruption Ratio on Quality of Experience (QoE) in Video Streaming
The volume of Internet video traffic which consists of downloaded or streamed video from the Internet is projected to increase from 42,029PB monthly in 2016 to 159,161PB monthly, in 2021, representing a 31% increase in t...
Hybrid Latin-Hyper-Cube-Hill-Climbing Method for Optimizing: Experimental Testing
A noticeable objective of this work is to experiment and test an optimization problem through comparing hill-climbing method with a hybrid method combining hill-climbing and Latin-hyper-cube. These two methods are going...