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The University of Michigan Library wanted to learn more about the kinds of searches its users were conducting through the “one search” search box on the Library Web site. Library staff conducted two investigations. A preliminary investigation in 2011 involved the manual review of the 100 most frequently occurring queries conducted through the site search box over the course of a month. Those 100 search terms accounted for 16 percent of total queries and were largely one-word searches for...
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In this paper, we report ongoing efforts in a large scale research project to develop methods for profiling individual Web search engine users by leveraging data recorded in the transaction logs of search engines. Our research aim is to investigate how completely one can profile a Web searcher using log data. Taking a broad brush approach, we present an array of profiling attributes to illustrate the spectrum of user characteristics possible from log data. Specifically, we present ongoing...
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This report summarises a workshop organised as a part of the EU-funded TrebleCLEF project entitled "Query Log Analysis: From Research to Best Practice" held on 27-28th May 2009 at the British Computer Science Offices in London, UK. The event involved 12 invited speakers from various academic and commercial institutions from around the world who are all involved, in some way, with query log analysis. A number of other people attended the event including local businesses and academic...
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Query reformulation is a key user behavior during Web search. Our research goal is to develop predictive models of query reformulation during Web searching. This article reports results from a study in which we automatically classified the query-reformulation patterns for 964,780 Web searching sessions, composed of 1,523,072 queries, to predict the next query reformulation. We employed an n-gram modeling approach to describe the probability of users transitioning from one query-reformulation...
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In this paper, we define and present a comprehensive classification of user intent for Web searching. The classification consists of three hierarchical levels of informational, navigational, and transactional intent. After deriving attributes of each, we then developed a software application that automatically classified queries using a Web search engine log of over a million and a half queries submitted by several hundred thousand users. Our findings show that more than 80% of Web queries...
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Over time, researchers have acknowledged the importance of understanding the users’ strategies in the design of search systems. However, when involving users in the comparison of search systems, methodological challenges still exist as researchers are pondering on how to handle the variability that human participants bring to the comparisons. This paper present methods for controlling the complexity of user-centered evaluations of search user interfaces through within subjects designs,...
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Most text classification techniques assume that manually labeled documents (corpora) can be easily obtained while learning text classifiers. However, labeled training documents are sometimes unavailable or inadequate even if they are available. The goal of this article is to present a self-learned approach to extract high-quality training documents from the Web when the required manually labeled documents are unavailable or of poor quality. To learn a text classifier automatically, we need...
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Accurate topical classification of user queries allows for increased effectiveness and efficiency in general-purpose Web search systems. Such classification becomes critical if the system must route queries to a subset of topic-specific and resource-constrained back-end databases. Successful query classification poses a challenging problem, as Web queries are short, thus providing few features. This feature sparseness, coupled with the constantly changing distribution and vocabulary of...
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Recording search histories, presenting them to the searcher, and building additional interface tools on them offer many opportunities for supporting user tasks in information seeking and use. This study investigated the use of search history information in legal information seeking. Qualitative methods were used to explore how attorneys and law librarians used their memory and external memory aids while searching for information and in transferring to information use. Based on the findings,...
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In this paper, we propose a query-categorization approach to facilitating the engineering process of constructing Web taxonomies. One primary step in taxonomy construction is to acquire the domain-specific terminology terms and the mapping between the subjects and these terms. We introduce a technique for categorizing Web query terms from the logs of on-line search services into a predefined subject taxonomy based on their supposed popular search interests. The obtained experimental results...
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Classic IR (information retrieval) is inherently predicated on users searching for information, the so-called "information need". But the need behind a web search is often not informational -- it might be navigational (give me the url of the site I want to reach) or transactional (show me sites where I can perform a certain transaction, e.g. shop, download a file, or find a map). We explore this taxonomy of web searches and discuss how global search engines evolved to deal with web-specific needs.
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Subject content analysis of Web query terms is essential to understand Web searching interests. Such analysis includes exploring search topics and observing changes in their frequency distributions with time. To provide a basis for in-depth analysis of users' search interests on a larger scale, this article presents a query categorization approach to automatically classifying Web query terms into broad subject categories. Because a query is short in length and simple in structure, its...
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Discussion of terms and how they are used in queries in information retrieval focuses on a transaction log analysis of queries posed on an Internet search service that isolated basic query structure syntactic patterns. Describes a linguistic model that classified Web queries and suggests implications for information retrieval system design. (Contains 9 references.) (Author/LRW)
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