A Taxonomy of Web Search
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1 A Taxonomy of Web Search by Andrei Broder 1
2 Overview Ø Motivation Ø Classic model for IR Ø Web-specific Needs Ø Taxonomy of Web Search Ø Evaluation Ø Evolution of Search Engines Ø Conclusions 2 1
3 Motivation Ø central tenet information need But : show me url of the site where I can find a map of New York I want to buy a new computer intend behind web search not always informational web-specific needs should be taken into account 3 2
4 Aims of this Paper Aims : Ø point out the difference between classic IR and web search Ø introduce and analyze a taxonomy of web searches Ø show how search engines deal with web-specific needs 4 3
5 Classic Model for IR Info need Query Corpus Matching Rules Query Refinement Results 5 4
6 Web-specific Needs Task Info need Verbal form Query Corpus Search Engine Query Refinement Results 6 5
7 A Taxonomy of Web Search Classification of web queries into 3 categories: 1. Informational (acquire some information assumed to be present on one or more web pages) 2. Navigational (to reach a particular site) 3. Transactional (perform some web-mediated activity) 7 6
8 1. Informational Queries Intent: acquire some information assumed to be present on one or more web pages Ø information is in static form Ø no further interaction is predicted 1. Where will WC 2018 be held? WC What is the current rank of Hannover 96? table Hannover
9 2. Navigational Queries Intent : to reach a particular site Ø user visited it in the past or assumes that it exists Ø known item search or home page finding task Ø only one right result 1. What is the official website of IBM? official website IBM 2. HP Store in Germany HP Germany 9 8
10 3. Transactional Queries Intent : perform some web-mediated activity Ø further interaction is expected Ø main categories: shopping, finding servers, downloading various types of files 1. I need an accommodation in Rome hotel Rome 2. I want to buy a new bed bed Ikea 10 9
11 Scenario Alice wants to buy a printer. Transactional Query Alice found 3 printers that she likes. She wants more information about them. Infomational Query Alice wants some information about firma Lexmark. She assumes that it has a site in Germany. Navigational Query Alice wants to download a document with a printer test. Transactional Query 11 10
12 Evaluation 2 Methods : Ø a survey of AltaVista users Ø presented to random users Ø users are self selected Ø a pop-up window with the questions Ø analysis of the query log at AltaVista 12 11
13 Survey Queries Ø to distinguish between navigational and non-navigational queries: Which of the following describes best what you are trying to do? 24,53 o % 68,41 o % I want to get to a specific website that I already have in mind I want a good site on this topic, but I don t have a specific site in mind 13 12
14 Survey Queries Ø to distinguish between transactional and non-transactional queries: Which of the following best describes why you conducted this search? 8,16 % o 5,46 % o 22,55 % o 57,19 % o I am shopping for something to buy on the Internet I am shopping for something to buy elsewhere than on the Internet I want to download a file (e.g. music, images, programs, etc.) None of these reasons 14 13
15 Survey Queries Ø to distinguish between informational and non-informational queries: Which of the following describes best what you are looking for? 14,83 o % 76,62 o % A site which is a collection of links to other sites regarding this topic The best site regarding this topic 15 14
16 Log Analysis Ø a random set of 1000 queries from the daily AltaVista log Ø only English queries Ø sexually oriented queries are removed Ø queries that are neither navigational, nor transactional are assumed to be informational 16 15
17 Summary Type of query User Survey Query Log Analysis Navigational 24,5% 20% Informational 39% 48% Transactional 36% 30% 17 16
18 Evolution of Search Engines First generation ( ) Ø on-page data, close to classic IR, mostly informational queries Ø AltaVista, Excite, WebCrawler, etc Second generation ( ) Ø off-page, use of web-specific data such as link analysis, anchor-text, and click-through data, informational and navigational queries Ø Google, DirectHit Third generation (2000-now) Ø attempt to ask the need behind a query, data from multiple sources, support for informational, navigational, transactional queries 18 17
19 Conclusion and Comments Ø web search is task-driven Ø search engines need to deal with different types of queries Ø subtle difference between the navigational and informational queries Ø some misleading in the evaluation part 19 18
20 Questions??? Thanx! 20 19
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