Research and application of VoD search engine based on Lucene

doi:10.3778/j.issn.1002-8331.2008.29.002

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (29): 8-10.DOI: 10.3778/j.issn.1002-8331.2008.29.002

• 博士论坛 • Previous Articles Next Articles

Research and application of VoD search engine based on Lucene

KUANG Zhen-guo^1,2,NI Hong²,JI Zhi-hui^1,2,LIU Lei^1,2

1.Graduate University of Chinese Academy of Sciences，Beijing 100039，China
2.National Network New Media Engineering Research Center，Institute of Acoustics，CAS，Beijing 100190，China

Received:2008-05-26 Revised:2008-06-23 Online:2008-10-11 Published:2008-10-11
Contact: KUANG Zhen-guo

一种基于Lucene的影片搜索引擎的研究和应用

匡振国^1,2,倪宏²,嵇智辉^1,2,刘磊^1,2

1.中国科学院研究生院，北京 100039
2.中国科学院声学研究所国家网络新媒体工程技术研究中心，北京 100190

通讯作者: 匡振国

Abstract

Abstract: Lucene is an excellent framework for search engine of open source code，and it has been widely used in the field of information retrieval.After analyzing the disadvantage of existing search engines in VoD portal，a word segmentation method supporting Chinese based on double character hash index algorithm is designed.With the use of the word segmentation method and Lucene tool lib，a VoD Quick video search engine is implemented，which not only supports Chinese search but also has the benefits of searching fast，easy expansion and so on.The simulation results show that the video search engine based on the Lucene designed in this paper has a good performance.

Key words: Lucene, search engine, double character hash index, Chinese word segmentation, inverted index

摘要： Lucene是一个优秀的开源搜索引擎框架，已经广泛应用于信息搜索领域。分析点播门户中现有的搜索引擎存在的不足，设计一种基于双字哈希算法支持中文的分词器，并利用该分词器和Lucene工具包，设计并实现了一个视频点播影片快速搜索引擎，它不仅支持中文检索，还具有搜索速度快、易于扩展等优点。仿真实验证明提出的基于Lucene的影片搜索引擎具有良好的性能。

关键词: Lucene, 搜索引擎, 双字哈希, 中文分词, 倒排索引

KUANG Zhen-guo^1,2,NI Hong²,JI Zhi-hui^1,2,LIU Lei^1,2. Research and application of VoD search engine based on Lucene[J]. Computer Engineering and Applications, 2008, 44(29): 8-10.

匡振国^1,2,倪宏²,嵇智辉^1,2,刘磊^1,2. 一种基于Lucene的影片搜索引擎的研究和应用[J]. 计算机工程与应用, 2008, 44(29): 8-10.

[1]	TU Wenbo, YUAN Zhenming, YU Kai. Convolutional Neural Networks Without Pooling Layer for Chinese Word Segmentation [J]. Computer Engineering and Applications, 2020, 56(2): 120-126.
[2]	SUN Baoshan, LI Wei. Recurrent Neural Network for Chinese Word Segmentation with Peephole-Connections [J]. Computer Engineering and Applications, 2019, 55(19): 160-165.
[3]	AN Zhaoxiang, QU Youli. Research on Inverted Index Compression Algorithm with Variable Coding Units [J]. Computer Engineering and Applications, 2019, 55(15): 82-88.
[4]	CHENG Yusi1, SHI Yuntao2. Domain specific Chinese word segmentation [J]. Computer Engineering and Applications, 2018, 54(17): 30-34.
[5]	YANG Heping1, CHEN Yu2, 3, ZHANG Zhiqiang1. Design and implementation of Web concise ontology-base vertical search engine [J]. Computer Engineering and Applications, 2017, 53(19): 257-264.
[6]	ZHAO Weifeng1，2, ZHANG Qin1. Automatic identification of address description in unstructured Chinese natural language [J]. Computer Engineering and Applications, 2016, 52(23): 19-24.
[7]	SHU Xiaowei, YANG Geng, NA Haiyang. Research on parallel crypt inverted index [J]. Computer Engineering and Applications, 2016, 52(20): 14-19.
[8]	ZHU Yanhui, LIU Jing, XU Yeqiang, TIAN Hailong, MA Jin. Chinese word segmentation research based on Conditional Random Field [J]. Computer Engineering and Applications, 2016, 52(15): 97-100.
[9]	DENG Xiaomei, WU Gang. Evaluating user satisfaction of search engine using click log [J]. Computer Engineering and Applications, 2015, 51(8): 245-249.
[10]	LU Hao, PANG Yong, LI Zengyuan. Storage and access of full waveform LiDAR data of LAS1.3 format based on inverted index [J]. Computer Engineering and Applications, 2015, 51(16): 243-247.
[11]	SHA Guanghua, CHEN Yong, ZHANG Changjiang. Application of read-write splitting technologies in operation support system [J]. Computer Engineering and Applications, 2015, 51(12): 107-110.
[12]	CAO Hongjiang, FU Kui. Research on clustering search method in collaborative filtering recommendation system [J]. Computer Engineering and Applications, 2014, 50(5): 16-20.
[13]	SHI Baoming1, HE Yuanxiang1, WU Chongzheng2. Research on search strategy of web spider in topic-oriented search engines [J]. Computer Engineering and Applications, 2014, 50(2): 116-119.
[14]	BAI Peifa1, WANG Chengliang1，2, XU Ling2. Scoring algorithm of similarity based on terms’ position feature combination for Lucene [J]. Computer Engineering and Applications, 2014, 50(2): 129-132.
[15]	WEI Renjia, WU Zhenqiang. Design and implementation of vertical search engine for education video resources [J]. Computer Engineering and Applications, 2014, 50(15): 113-116.

Research and application of VoD search engine based on Lucene

一种基于Lucene的影片搜索引擎的研究和应用

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics