Mining of Massive Web Data第54讲Web信息检索简介更多资料：http://web.stanford.edu/class/cs276/武汉理工大学计算机科学与技术学院
Mining of Massive Web Data 更多资料：h1p://web.stanford.edu/class/cs276/ ᦇᓒᑀӨದᴺ ᒫ54ᦖ Webמ௳༄ᔱᓌՕ
计贸机科学与技术学院第14讲Web信息检索简介IntroductionInformationRetrievalWeb SearchIRHistory武铺理工大学
ᒫ14ᦖ Web מ௳༄ᔱᓌՕ Introduc@on Web Search Informa@on Retrieval IR History
计算机科学与技术学院InformationRetrieval (IR).The indexing and retrieval of textual documents.? Searching for pages on the World Wide Web is the most recent“killer app."? Concerned firstly with retrieving relevant documents to aquery.? Concerned secondly with retrieving from large sets ofdocumentsefficiently武铺理工大学
Information Retrieval (IR) • The indexing and retrieval of textual documents. • Searching for pages on the World Wide Web is the most recent “killer app.” • Concerned firstly with retrieving relevant documents to a query. • Concerned secondly with retrieving from large sets of documents efficiently
计等机科学与技术学院Typical IR TaskGiven:A corpus of textual natural-language documentsA user query in the form of a textual stringFind:A ranked set of documents that are relevant to thequery.武铺理工大学
Typical IR Task • Given: - A corpus of textual natural-language documents. - A user query in the form of a textual string. • Find: - A ranked set of documents that are relevant to the query
计算机科学与技术学院IRSystemDocumentcorpusQueryIRStringSystem1. Docl2. Doc2Ranked3. Doc3Documents武铺理工大学
IR System IR System Query String Document corpus Ranked Documents 1. Doc1 2. Doc2 3. Doc3 .