Monolingual Information Retrieval using Terrier: FIRE 2010 Experiments based on n-gram indexing

被引：1

作者：

Vishwakarma, Santosh K. ^{[1
]}

Lakhtaria, Karna Ljit I. ^{[2
]}

Bhatnagar, Divya ^{[3
]}

Sharma, Akhilesh K. ^{[3
]}

机构：

[1] Gyan Ganga Inst Technol & Sci, Jabalpur, Madhya Pradesh, India

[2] Auro Univ, Surat, Gujarat, India

[3] SPSU, Udaipur 313001, Rajasthan, India

来源：

3RD INTERNATIONAL CONFERENCE ON RECENT TRENDS IN COMPUTING 2015 (ICRTC-2015) | 2015年 / 57卷

关键词：

Information Retrieval; N-gram; MAP; Pruning; Hindi Monolingual; TEXT;

D O I：

10.1016/j.procs.2015.07.484

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

N-gram based indexing technique has been proved as a useful technique for efficient document retrieval. We applied the n-gram approach and performed experiments in Hindi language text collections. The experiments are performed on the dataset of FIRE 2010 Hindi text collections. We used the Terrier open search engine for experimental purpose. Our experiments state that 4-gram gives the best results among all n-grams of different length. The results show an increase in value of mean average precision. (C) 2015 The Authors. Published by Elsevier B.V.

引用

页码：815 / 820

页数：6

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