{"title":"Building a Self-Contained Search Engine in the Browser","authors":"Jimmy J. Lin","doi":"10.1145/2808194.2809478","DOIUrl":null,"url":null,"abstract":"JavaScript engines inside modern web browsers are capable of running sophisticated multi-player games, rendering impressive 3D scenes, and supporting complex, interactive visualizations. Can this processing power be harnessed for information retrieval? This paper explores the feasibility of building a JavaScript search engine that runs completely self-contained on the client side within the browser - this includes building the inverted index, gathering terms statistics for scoring, and performing query evaluation. The design takes advantage of the IndexDB API, which is implemented by the LevelDB key{value store inside Google's Chrome browser. Experiments show that although the performance of the JavaScript prototype falls far short of the open-source Lucene search engine, it is sufficiently responsive for interactive applications. This feasibility demonstration opens the door to interesting applications and architectures.","PeriodicalId":440325,"journal":{"name":"Proceedings of the 2015 International Conference on The Theory of Information Retrieval","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2015 International Conference on The Theory of Information Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2808194.2809478","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
JavaScript engines inside modern web browsers are capable of running sophisticated multi-player games, rendering impressive 3D scenes, and supporting complex, interactive visualizations. Can this processing power be harnessed for information retrieval? This paper explores the feasibility of building a JavaScript search engine that runs completely self-contained on the client side within the browser - this includes building the inverted index, gathering terms statistics for scoring, and performing query evaluation. The design takes advantage of the IndexDB API, which is implemented by the LevelDB key{value store inside Google's Chrome browser. Experiments show that although the performance of the JavaScript prototype falls far short of the open-source Lucene search engine, it is sufficiently responsive for interactive applications. This feasibility demonstration opens the door to interesting applications and architectures.