940 resultados para 080505 Web Technologies (excl. Web Search)


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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 state to another to predict their next state. We developed first-, second-, third-, and fourth-order models and evaluated each model for accuracy of prediction, coverage of the dataset, and complexity of the possible pattern set. The results show that Reformulation and Assistance account for approximately 45% of all query reformulations; furthermore, the results demonstrate that the first- and second-order models provide the best predictability, between 28 and 40% overall and higher than 70% for some patterns. Implications are that the n-gram approach can be used for improving searching systems and searching assistance.

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With the size and state of the Internet today, a good quality approach to organizing this mass of information is of great importance. Clustering web pages into groups of similar documents is one approach, but relies heavily on good feature extraction and document representation as well as a good clustering approach and algorithm. Due to the changing nature of the Internet, resulting in a dynamic dataset, an incremental approach is preferred. In this work we propose an enhanced incremental clustering approach to develop a better clustering algorithm that can help to better organize the information available on the Internet in an incremental fashion. Experiments show that the enhanced algorithm outperforms the original histogram based algorithm by up to 7.5%.

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Current multimedia Web search engines still use keywords as the primary means to search. Due to the richness in multimedia contents, general users constantly experience some difficulties in formulating textual queries that are representative enough for their needs. As a result, query reformulation becomes part of an inevitable process in most multimedia searches. Previous Web query formulation studies did not investigate the modification sequences and thus can only report limited findings on the reformulation behavior. In this study, we propose an automatic approach to examine multimedia query reformulation using large-scale transaction logs. The key findings show that search term replacement is the most dominant type of modifications in visual searches but less important in audio searches. Image search users prefer the specified search strategy more than video and audio users. There is also a clear tendency to replace terms with synonyms or associated terms in visual queries. The analysis of the search strategies in different types of multimedia searching provides some insights into user’s searching behavior, which can contribute to the design of future query formulation assistance for keyword-based Web multimedia retrieval systems.

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Searching for multimedia is an important activity for users of Web search engines. Studying user's interactions with Web search engine multimedia buttons, including image, audio, and video, is important for the development of multimedia Web search systems. This article provides results from a Weblog analysis study of multimedia Web searching by Dogpile users in 2006. The study analyzes the (a) duration, size, and structure of Web search queries and sessions; (b) user demographics; (c) most popular multimedia Web searching terms; and (d) use of advanced Web search techniques including Boolean and natural language. The current study findings are compared with results from previous multimedia Web searching studies. The key findings are: (a) Since 1997, image search consistently is the dominant media type searched followed by audio and video; (b) multimedia search duration is still short (>50% of searching episodes are <1 min), using few search terms; (c) many multimedia searches are for information about people, especially in audio search; and (d) multimedia search has begun to shift from entertainment to other categories such as medical, sports, and technology (based on the most repeated terms). Implications for design of Web multimedia search engines are discussed.

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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 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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As Web searching becomes more prolific for information access worldwide, we need to better understand users’ Web searching behaviour and develop better models of their interaction with Web search systems. Web search modelling is a significant and important area of Web research. Searching on the Web is an integral element of information behaviour and human–computer interaction. Web searching includes multitasking processes, the allocation of cognitive resources among several tasks, and shifts in cognitive, problem and knowledge states. In addition to multitasking, cognitive coordination and cognitive shifts are also important, but are under-explored aspects of Web searching. During the Web searching process, beyond physical actions, users experience various cognitive activities. Interactive Web searching involves many users’ cognitive shifts at different information behaviour levels. Cognitive coordination allows users to trade off the dependences among multiple information tasks and the resources available. Much research has been conducted into Web searching. However, few studies have modelled the nature of and relationship between multitasking, cognitive coordination and cognitive shifts in the Web search context. Modelling how Web users interact with Web search systems is vital for the development of more effective Web IR systems. This study aims to model the relationship between multitasking, cognitive coordination and cognitive shifts during Web searching. A preliminary theoretical model is presented based on previous studies. The research is designed to validate the preliminary model. Forty-two study participants were involved in the empirical study. A combination of data collection instruments, including pre- and post-questionnaires, think-aloud protocols, search logs, observations and interviews were employed to obtain users’ comprehensive data during Web search interactions. Based on the grounded theory approach, qualitative analysis methods including content analysis and verbal protocol analysis were used to analyse the data. The findings were inferred through an analysis of questionnaires, a transcription of think-aloud protocols, the Web search logs, and notes on observations and interviews. Five key findings emerged. (1) Multitasking during Web searching was demonstrated as a two-dimensional behaviour. The first dimension was represented as multiple information problems searching by task switching. Users’ Web searching behaviour was a process of multiple tasks switching, that is, from searching on one information problem to searching another. The second dimension of multitasking behaviour was represented as an information problem searching within multiple Web search sessions. Users usually conducted Web searching on a complex information problem by submitting multiple queries, using several Web search systems and opening multiple windows/tabs. (2) Cognitive shifts were the brain’s internal response to external stimuli. Cognitive shifts were found as an essential element of searching interactions and users’ Web searching behaviour. The study revealed two kinds of cognitive shifts. The first kind, the holistic shift, included users’ perception on the information problem and overall information evaluation before and after Web searching. The second kind, the state shift, reflected users’ changes in focus between the different cognitive states during the course of Web searching. Cognitive states included users’ focus on the states of topic, strategy, evaluation, view and overview. (3) Three levels of cognitive coordination behaviour were identified: the information task coordination level, the coordination mechanism level, and the strategy coordination level. The three levels of cognitive coordination behaviour interplayed to support multiple information tasks switching. (4) An important relationship existed between multitasking, cognitive coordination and cognitive shifts during Web searching. Cognitive coordination as a management mechanism bound together other cognitive processes, including multitasking and cognitive shifts, in order to move through users’ Web searching process. (5) Web search interaction was shown to be a multitasking process which included information problems ordering, task switching and task and mental coordinating; also, at a deeper level, cognitive shifts took place. Cognitive coordination was the hinge behaviour linking multitasking and cognitive shifts. Without cognitive coordination, neither multitasking Web searching behaviour nor the complicated mental process of cognitive shifting could occur. The preliminary model was revisited with these empirical findings. A revised theoretical model (MCC Model) was built to illustrate the relationship between multitasking, cognitive coordination and cognitive shifts during Web searching. Implications and limitations of the study are also discussed, along with future research work.

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User-Web interactions have emerged as an important area of research in the field of information science. In this study, we investigate the effects of users’ cognitive styles on their Web navigational styles and information processing strategies. We report results from the analyses of 594 minutes recorded Web search sessions of 18 participants engaged in 54 scenario-based search tasks. We use questionnaires, cognitive style test, Web session logs and think-aloud as the data collection instruments. We classify users’ cognitive styles as verbalisers and imagers based on Riding’s (1991) Cognitive Style Analysis test. Two classifications of navigational styles and three categories of information processing strategies are identified. Our study findings show that there exist relationships between users’ cognitive style, and their navigational styles and information processing strategies. Verbal users seem to display sporadic navigational styles, and adopt a scanning strategy to understand the content of the search result page, while imagery users follow a structured navigational style and reading approach. We develop a matrix and a model that depicts the relationships between users’ cognitive styles, and their navigational style and information processing strategies. We discuss how the findings from this study could help search engine designers to provide an adaptive navigation support to users.

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As more and more information is available on the Web finding quality and reliable information is becoming harder. To help solve this problem, Web search models need to incorporate users’ cognitive styles. This paper reports the preliminary results from a user study exploring the relationships between Web users’ searching behavior and their cognitive style. The data was collected using a questionnaire, Web search logs and think-aloud strategy. The preliminary findings reveal a number of cognitive factors, such as information searching processes, results evaluations and cognitive style, having an influence on users’ Web searching behavior. Among these factors, the cognitive style of the user was observed to have a greater impact. Based on the key findings, a conceptual model of Web searching and cognitive styles is presented.