Search (5 results, page 1 of 1)

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Abstract

Purpose - The purpose of this paper is to examine the way in which end user searching on the web has become the primary method of locating digital images for many people. This paper seeks to investigate how users structure these image queries. Design/methodology/approach - This study investigates the structure and formation of image queries on the web by mapping a sample of web queries to three known query classification schemes for image searching (i.e. Enser and McGregor, Jörgensen, and Chen). Findings - The results indicate that the features and attributes of web image queries differ relative to image queries utilized on other information retrieval systems and by other user populations. This research points to the need for five additional attributes (i.e. collections, pornography, presentation, URL, and cost) in order to classify web image queries, which were not present in any of the three prior classification schemes. Research limitations/implications - Patterns in web searching for image content do emerge that inform the design of web-based multimedia systems, namely, that there is a high interest in locating image collections by web searchers. Objects and people images are the predominant interest for web searchers. Cost is a factor for web searching. This knowledge of the structure of web image queries has implications for the design of image information retrieval systems and repositories, especially in the area of automatic tagging of images with metadata. Originality/value - This is the first research that examines whether or not one can apply image query classifications schemes to web image queries.

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Abstract

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 are informational in nature, with about 10% each being navigational and transactional. In order to validate the accuracy of our algorithm, we manually coded 400 queries and compared the results from this manual classification to the results determined by the automated method. This comparison showed that the automatic classification has an accuracy of 74%. Of the remaining 25% of the queries, the user intent is vague or multi-faceted, pointing to the need for probabilistic classification. We discuss how search engines can use knowledge of user intent to provide more targeted and relevant results in Web searching.

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Abstract

Many people turn to their social networks to find information through the practice of question and answering. We believe it is necessary to use different answering strategies based on the type of questions to accommodate the different information needs. In this research, we propose the ASK taxonomy that categorizes questions posted on social networking sites into three types according to the nature of the questioner's inquiry of accuracy, social, or knowledge. To automatically decide which answering strategy to use, we develop a predictive model based on ASK question types using question features from the perspectives of lexical, topical, contextual, and syntactic as well as answer features. By applying the classifier on an annotated data set, we present a comprehensive analysis to compare questions in terms of their word usage, topical interests, temporal and spatial restrictions, syntactic structure, and response characteristics. Our research results show that the three types of questions exhibited different characteristics in the way they are asked. Our automatic classification algorithm achieves an 83% correct labeling result, showing the value of the ASK taxonomy for the design of social question and answering systems.

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Abstract

In previous articles, we reported the state of Web searching in 1997 (Jansen, Spink, & Saracevic, 2000) and in 1999 (Spink, Wolfram, Jansen, & Saracevic, 2001). Such snapshot studies and statistics on Web use appear regularly (OCLC, 1999), but provide little information about Web searching trends. In this article, we compare and contrast results from our two previous studies of Excite queries' data sets, each containing over 1 million queries submitted by over 200,000 Excite users collected on 16 September 1997 and 20 December 1999. We examine how public Web searching changing during that 2-year time period. As Table 1 shows, the overall structure of Web queries in some areas did not change, while in others we see change from 1997 to 1999. Our comparison shows how Web searching changed incrementally and also dramatically. We see some moves toward greater simplicity, including shorter queries (i.e., fewer terms) and shorter sessions (i.e., fewer queries per user), with little modification (addition or deletion) of terms in subsequent queries. The trend toward shorter queries suggests that Web information content should target specific terms in order to reach Web users. Another trend was to view fewer pages of results per query. Most Excite users examined only one page of results per query, since an Excite results page contains ten ranked Web sites. Were users satisfied with the results and did not need to view more pages? It appears that the public continues to have a low tolerance of wading through retrieved sites. This decline in interactivity levels is a disturbing finding for the future of Web searching. Queries that included Boolean operators were in the minority, but the percentage increased between the two time periods. Most Boolean use involved the AND operator with many mistakes. The use of relevance feedback almost doubled from 1997 to 1999, but overall use was still small. An unusually large number of terms were used with low frequency, such as personal names, spelling errors, non-English words, and Web-specific terms, such as URLs. Web query vocabulary contains more words than found in large English texts in general. The public language of Web queries has its own and unique characteristics. How did Web searching topics change from 1997 to 1999? We classified a random sample of 2,414 queries from 1997 and 2,539 queries from 1999 into 11 categories (Table 2). From 1997 to 1999, Web searching shifted from entertainment, recreation and sex, and pornography, preferences to e-commerce-related topics under commerce, travel, employment, and economy. This shift coincided with changes in information distribution on the publicly indexed Web.

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Date

22. 3.2009 17:49:11