Lovely Sharma ¹, Vijay Dhir ², Kamaljeet Kaur ³

Affiliations
1 Punjab Technical University, Kapurthala Road, Jalandhar – 144601, Punjab, IN
2 St. Soldier Institute of Engineering and Technology, Jalandhar – 144622, Punjab, IN
3 Department of Computer Science, D. A.V. College, Amritsar – 143001, Punjab, IN

Abstract

Objective: Currently, the user is rely on the results of the Google search i.e. lengthy documents, web links etc. So, Question Answering (QA) dialogue system becomes more vital to access the succinct answers in a jiffy. Methods: The main focus is on Query Processing based on partial semantic and syntactic analysis and keyword based approach. The major module is Dialogue Manager which is responsible to communicate between the User and the System to resolve anaphora and Co-reference problems. Findings: The existing Indian Railway system is based on clicking system which is more time consuming. Thus, proposed QA dialogue system provides specific and concise answers to users. The results are encouraging and a motivation for further research in this field. The proposed system restricted to provide answers of related queries but further extension of the system can also include replies related arrival time, departure time over the phone etc.

Keywords

Dialogue based Question-Answering System, Dialogue Manager, Semantic Analysis

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Lovely Sharma ¹, Vijay Dhir ², Kamaljeet Kaur ³

Affiliations
1 Department of Computer Science and IT, Doaba College, Jalandhar - 144001, Punjab, IN
2 St. Soldier Institute of Engineering & Technology, Jalandhar - 144622, Punjab, IN
3 Department of Computer Science, D.A.V College, Amritsar - 143001, Punjab, IN

Abstract

Objectives: The plethora of information available on the web makes it difficult to search for a specific and suitable query. So, Question Answering dialogue system becomes helpful to provide precise and short answers to users instead of lengthy documents or passages. Method: The main focus is on keyword based approach and partial linguistic analysis to process the query. The main component is Dialogue Manager which clarifies the conversation between user and system to resolve the elliptical and anaphoric problems. Findings/ Application: The paper is based upon the development of Question answering dialogue system in Hindi language for the domain of Railways. The study is restricted to Northern India alone. The existing system of Indian railway does not support Question Answering system while this novel system will provide anytime anywhere facility of enquiry about railway. The implemented system is quite simple, interactive and easy to use such that end user can ask the query using Hindi transliteration. The results are quite satisfactory as precision and recall values are 98% and 97% respectively.

Keywords

Dialogue Manager, Partial Syntactic and Semantic Analysis, Query Processing, Question Answering Railway System.

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Harpreet Kaur ¹, Vijay Dhir ²

Affiliations
1 Department of Computer Science and Engineering, Punjab Technical University, Kapurthala, Punjab - 144601, IN
2 Sant Baba Bhag Singh Insitute of Engineering & Technology, Jalandhar, Punjab - 144020, IN

Abstract

Objectives: This paper presents a new feature extractor which we named as Local Color Oppugnant Mesh Extrema Patterns (LCOMeEP) for retrieval of images. Methods/Statistical Analysis: The suggested method gathers the colortexture statistics among the RGB (Red, Green and Blue) and gray scale of the given image. The color-texture statistics is extracted based on mesh extrema which assembles the relationship among the neighbors using extrema. Findings: The proposed method is diverse from the Directional Local Extrema Patterns (DLEP) collect the directional information which is based on local extrema in an image. Whereas the method presented in this paper, (LCOMeEP) gathers the mesh extremas amid the RgG (red, gray, green), GgB (green, gray, blue) and BgR (blue, gray, red) spaces. The enactment of the presented technique is amended by assimilating the LCOMeEPs with histograms of HSV (hue, saturation, value). The enactment of the research work is estimated by simulating on standard data sets, Corel-5K and Corel-10K in context of recall, precision, Average Retrieval Rate (ARR) and Average Retrieval Precision (ARP). Application/Improvements: The outcome after inspection illustrates a substantial enhancement as related to the contemporary features for image retrieval.

Keywords

Image Retrieval, Local Binary Patterns (LBP), Local Extrema Patterns, Local Oppugnant Patterns, Pattern Recognition, Texture

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