930 resultados para Web Search Behaviour
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This article explores consumer Web-search satisfaction. It commences with a brief overview of the concepts consumer information search and consumer satisfaction. Consumer Web adoption issues are then briefly discussed and the importance of consumer search satisfaction is highlighted in relation to the adoption of the Web as an additional source of consumer information. Research hypotheses are developed and the methodology of a large scale consumer experiment to record consumer Web search behaviour is described. The hypotheses are tested and the data explored in relation to post-Web-search satisfaction. The results suggest that consumer post-Web-search satisfaction judgments may be derived from subconscious judgments of Web search efficiency, an empirical calculation of which is problematic in unlimited information environments such as the Web. The results are discussed and a future research agenda is briefly outlined.
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When publishing information on the web, one expects it to reach all the people that could be interested in. This is mainly achieved with general purpose indexing and search engines like Google which is the most used today. In the particular case of geographic information (GI) domain, exposing content to mainstream search engines is a complex task that needs specific actions. In many occasions it is convenient to provide a web site with a specially tailored search engine. Such is the case for on-line dictionaries (wikipedia, wordreference), stores (amazon, ebay), and generally all those holding thematic databases. Due to proliferation of these engines, A9.com proposed a standard interface called OpenSearch, used by modern web browsers to manage custom search engines. Geographic information can also benefit from the use of specific search engines. We can distinguish between two main approaches in GI retrieval information efforts: Classical OGC standardization on one hand (CSW, WFS filters), which are very complex for the mainstream user, and on the other hand the neogeographer’s approach, usually in the form of specific APIs lacking a common query interface and standard geographic formats. A draft ‘geo’ extension for OpenSearch has been proposed. It adds geographic filtering for queries and recommends a set of simple standard response geographic formats, such as KML, Atom and GeoRSS. This proposal enables standardization while keeping simplicity, thus covering a wide range of use cases, in both OGC and the neogeography paradigms. In this article we will analyze the OpenSearch geo extension in detail and its use cases, demonstrating its applicability to both the SDI and the geoweb. Open source implementations will be presented as well
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The web is continuously evolving into a collection of many data, which results in the interest to collect and merge these data in a meaningful way. Based on that web data, this paper describes the building of an ontology resting on fuzzy clustering techniques. Through continual harvesting folksonomies by web agents, an entire automatic fuzzy grassroots ontology is built. This self-updating ontology can then be used for several practical applications in fields such as web structuring, web searching and web knowledge visualization.A potential application for online reputation analysis, added value and possible future studies are discussed in the conclusion.
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Introduction Current empirical findings indicate that the efficiency of decision making (both for experts and near-experts) in simple situations is reduced under increased stress (Wilson, 2008). Explaining the phenomenon, the Attentional Control Theory (ACT, Eysenck et al., 2007) postulates an impairment of attentional processes resulting in a less efficient processing of visual information. From a practitioner’s perspective, it would be highly relevant to know whether this phenomenon can also be found in complex sport situations like in the game of football. Consequently, in the present study, decision making of football players was examined under regular vs. increased anxiety conditions. Methods 22 participants (11 experts and 11 near-experts) viewed 24 complex football situations (counterbalanced) in two anxiety conditions from the perspective of the last defender. They had to decide as fast and accurate as possible on the next action of the player in possession (options: shot on goal, dribble or pass to a designated team member) for equal numbers of trials in a near and far distance condition (based on the position of the player in possession). Anxiety was manipulated via a competitive environment, false feedback as well as ego threats. Decision time and accuracy, gaze behaviour (e.g., fixation duration on different locations) as well as state anxiety and mental effort were used as dependent variables and analysed with 2 (expertise) x 2 (distance) x 2 (anxiety) ANOVAs with repeated measures on the last two factors. Besides expertise differences, it was hypothesised that, based on ACT, increased anxiety reduces performance efficiency and impairs gaze behaviour. Results and Discussion Anxiety was manipulated successfully, indicated by higher ratings of state anxiety, F(1, 20) = 13.13, p < .01, ηp2 = .40. Besides expertise differences in decision making – experts responded faster, F(1, 20) = 11.32, p < .01, ηp2 = .36, and more accurate, F(1,20) = 23.93, p < .01, ηp2 = .55, than near-experts – decision time, F(1, 20) = 9.29, p < .01, ηp2 = .32, and mental effort, F(1, 20) = 7.33, p = .01, ηp2 = .27, increased for both groups in the high anxiety condition. This result confirms the ACT assumption that processing efficiency is reduced when being anxious. Replicating earlier findings, a significant expertise by distance interaction could be observed, F(1, 18) = 18.53, p < .01, ηp2 = .51), with experts fixating longer on the player in possession or the ball in the near distance and longer on other opponents, teammates and free space in the far distance condition. This shows that experts are able to adjust their gaze behaviour to affordances of displayed playing patterns. Additionally, a three way interaction was found, F(1, 18) = 7.37 p = .01, ηp2 = .29, revealing that experts utilised a reduced number of fixations in the far distance condition when being anxious indicating a reduced ability to pick up visual information. Since especially the visual search behaviour of experts was impaired, the ACT prediction that particularly top-down processes are affected by anxiety could be confirmed. Taken together, the results show that sports performance is negatively influenced by anxiety since longer response times, higher mental effort and inefficient visual search behaviour were observed. From a practitioner’s perspective, this finding might suggest preferring (implicit) perceptual cognitive training; however, this recommendation needs to be empirically supported in intervention studies. References: Eysenck, M. W., Derakshan, N., Santos, R., & Calvo, M. G. (2007). Anxiety and cognitive performance: Attentional control theory. Emotion, 7, 336-353. Wilson, M. (2008). From processing efficiency to attentional control: A mechanistic account of the anxiety-performance relationship. Int. Review of Sport and Exercise Psychology, 1, 184-201.
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Based on the Attentional Control Theory (ACT; Eysenck et al., 2007), performance efficiency is decreased in high-anxiety situations because worrying thoughts compete for attentional resources. A repeated-measures design (high/low state anxiety and high/low perceptual task demands) was used to test ACT explanations. Complex football situations were displayed to expert and non-expert football players in a decision making task in a controlled laboratory setting. Ratings of state anxiety and pupil diameter measures were used to check anxiety manipulations. Dependent variables were verbal response time and accuracy, mental effort ratings and visual search behavior (e.g., visual search rate). Results confirmed that an anxiety increase, indicated by higher state-anxiety ratings and larger pupil diameters, reduced processing efficiency for both groups (higher response times and mental effort ratings). Moreover, high task demands reduced the ability to shift attention between different locations for the expert group in the high anxiety condition only. Since particularly experts, who were expected to use more top-down strategies to guide visual attention under high perceptual task demands, showed less attentional shifts in the high compared to the low anxiety condition, as predicted by ACT, anxiety seems to impair the shifting function by interrupting the balance between top-down and bottom-up processes.
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Einleitung Aktuelle empirische Befunde deuten darauf hin, dass Sportler/innen durch Stress und erhöhte Angst eine reduzierte Effizienz bei der Entscheidungsfindung aufweisen (Wilson, 2008). Erklärt werden kann dieser Befund durch die Attentional-Control-Theory (ACT, Eysenck et al., 2007), die postuliert, dass aufmerksamkeitslenkende Prozesse unter Angst gestört werden. Um diese Annahme für komplexe Situationen im Sport zu prüfen, wurden Fußballspieler unter erhöhten und regulären Druckbedingungen verglichen. Methode Je 11 Experten und Nicht-Experten hatten aus der Perspektive des Abwehrspielers die Aufgabe, in zwei mal 24 Spielsituationen so schnell und korrekt wie möglich verbal anzugeben, welche Aktion der ballführende Spieler (in naher vs. ferner Spielsituation) nach Ausblendung der Szene ausführen wird. Während im ersten Block der Druck nicht erhöht wurde, wurden Druckbedingungen im zweiten Block u.a. durch eine Wettkampfsituation und „falscher“ Ergebnisrückmeldung gesteigert. Entscheidungs- und Blickverhalten (u.a. Anzahl Fixationen), Pupillengröße, Zustandsangst und „Mental Effort“ (Wilson, 2008) wurden erfasst. Neben Expertiseunterschieden wurde erwartet, dass erhöhte Angst die Entscheidungseffizienz sowie das Blickverhalten stört (ACT-Annahme), was mit 2 (Experten/Nicht-Experten) x 2 (nahe/ferne Spielsituation) x 2 (hohe/reguläre Druckbedingung) ANOVAs (? = .05) mit Messwiederholungen auf den letzten beiden Faktoren geprüft wurde. Ergebnisse Druckmanipulationen führten zu höherer Zustandsangst und größeren Pupillendurchmessern. Neben Expertiseunterschieden – Experten antworteten schneller, korrekter und zeigten ein situationsangepasstes visuelles Suchverhalten – wiesen beide Gruppen in Drucksituationen längere Antwortzeiten und höheren Mental Effort auf. Erhöhter Druck führte bei Experten zur Reduktion der Fixationsortwechsel für ferne Spielsituationen. Nicht-Experten differenzierten ihr Suchverhalten weder zwischen Bedingungen noch für Spielsituationen. Diskussion Die Resultate bestätigen die ACT-Annahme, dass Angst und Stress die sportliche Leistung durch längere Reaktionszeiten, höhere kognitive Anstrengung und ein teilweise ineffizientes visuelles Suchverhalten negativ beeinflusst. Eine gestörte Balance zwischen Top-Down und Bottom-Up-Prozessen könnte die Ursache sein (Eysenck et al., 2007). Literatur Eysenck, M. W., Derakshan, N., Santos, R., & Calvo, M. G. (2007). Anxiety and cognitive performance: Attentional control theory. Emotion, 7, 336–353. Wilson, M. (2008). From processing efficiency to attentional control: A mechanistic account of the anxiety-performance relationship. International Review of Sport and Exercise Psychology, 1, 184– 201. 2 Vorträge und Poster
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The role of gender differences in the consumption of goods and services is well established in many areas of consumer behaviour and computer use and yet there has been only limited research into such gender-based differences in the information search behaviour of Internet users. This paper reports the gender-based results of an exploratory study of consumer external information search of the web. The study investigated consumer characteristics, web search behaviour, and the post web search outcomes of purchase decision status and consumer judgements of search usefulness and satisfaction. Gender-based differences are reported in all three areas. Consideration of the results suggests they are issues which could inhibit the adoption of online purchasing by female web users. The implications of these results are discussed and a future research agenda proposed.
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Question Answering systems that resort to the Semantic Web as a knowledge base can go well beyond the usual matching words in documents and, preferably, find a precise answer, without requiring user help to interpret the documents returned. In this paper, the authors introduce a Dialogue Manager that, through the analysis of the question and the type of expected answer, provides accurate answers to the questions posed in Natural Language. The Dialogue Manager not only represents the semantics of the questions, but also represents the structure of the discourse, including the user intentions and the questions context, adding the ability to deal with multiple answers and providing justified answers. The authors’ system performance is evaluated by comparing with similar question answering systems. Although the test suite is slight dimension, the results obtained are very promising.
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Current-day web search engines (e.g., Google) do not crawl and index a significant portion of theWeb and, hence, web users relying on search engines only are unable to discover and access a large amount of information from the non-indexable part of the Web. Specifically, dynamic pages generated based on parameters provided by a user via web search forms (or search interfaces) are not indexed by search engines and cannot be found in searchers’ results. Such search interfaces provide web users with an online access to myriads of databases on the Web. In order to obtain some information from a web database of interest, a user issues his/her query by specifying query terms in a search form and receives the query results, a set of dynamic pages that embed required information from a database. At the same time, issuing a query via an arbitrary search interface is an extremely complex task for any kind of automatic agents including web crawlers, which, at least up to the present day, do not even attempt to pass through web forms on a large scale. In this thesis, our primary and key object of study is a huge portion of the Web (hereafter referred as the deep Web) hidden behind web search interfaces. We concentrate on three classes of problems around the deep Web: characterization of deep Web, finding and classifying deep web resources, and querying web databases. Characterizing deep Web: Though the term deep Web was coined in 2000, which is sufficiently long ago for any web-related concept/technology, we still do not know many important characteristics of the deep Web. Another matter of concern is that surveys of the deep Web existing so far are predominantly based on study of deep web sites in English. One can then expect that findings from these surveys may be biased, especially owing to a steady increase in non-English web content. In this way, surveying of national segments of the deep Web is of interest not only to national communities but to the whole web community as well. In this thesis, we propose two new methods for estimating the main parameters of deep Web. We use the suggested methods to estimate the scale of one specific national segment of the Web and report our findings. We also build and make publicly available a dataset describing more than 200 web databases from the national segment of the Web. Finding deep web resources: The deep Web has been growing at a very fast pace. It has been estimated that there are hundred thousands of deep web sites. Due to the huge volume of information in the deep Web, there has been a significant interest to approaches that allow users and computer applications to leverage this information. Most approaches assumed that search interfaces to web databases of interest are already discovered and known to query systems. However, such assumptions do not hold true mostly because of the large scale of the deep Web – indeed, for any given domain of interest there are too many web databases with relevant content. Thus, the ability to locate search interfaces to web databases becomes a key requirement for any application accessing the deep Web. In this thesis, we describe the architecture of the I-Crawler, a system for finding and classifying search interfaces. Specifically, the I-Crawler is intentionally designed to be used in deepWeb characterization studies and for constructing directories of deep web resources. Unlike almost all other approaches to the deep Web existing so far, the I-Crawler is able to recognize and analyze JavaScript-rich and non-HTML searchable forms. Querying web databases: Retrieving information by filling out web search forms is a typical task for a web user. This is all the more so as interfaces of conventional search engines are also web forms. At present, a user needs to manually provide input values to search interfaces and then extract required data from the pages with results. The manual filling out forms is not feasible and cumbersome in cases of complex queries but such kind of queries are essential for many web searches especially in the area of e-commerce. In this way, the automation of querying and retrieving data behind search interfaces is desirable and essential for such tasks as building domain-independent deep web crawlers and automated web agents, searching for domain-specific information (vertical search engines), and for extraction and integration of information from various deep web resources. We present a data model for representing search interfaces and discuss techniques for extracting field labels, client-side scripts and structured data from HTML pages. We also describe a representation of result pages and discuss how to extract and store results of form queries. Besides, we present a user-friendly and expressive form query language that allows one to retrieve information behind search interfaces and extract useful data from the result pages based on specified conditions. We implement a prototype system for querying web databases and describe its architecture and components design.
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This study examines the efficiency of search engine advertising strategies employed by firms. The research setting is the online retailing industry, which is characterized by extensive use of Web technologies and high competition for market share and profitability. For Internet retailers, search engines are increasingly serving as an information gateway for many decision-making tasks. In particular, Search engine advertising (SEA) has opened a new marketing channel for retailers to attract new customers and improve their performance. In addition to natural (organic) search marketing strategies, search engine advertisers compete for top advertisement slots provided by search brokers such as Google and Yahoo! through keyword auctions. The rationale being that greater visibility on a search engine during a keyword search will capture customers' interest in a business and its product or service offerings. Search engines account for most online activities today. Compared with the slow growth of traditional marketing channels, online search volumes continue to grow at a steady rate. According to the Search Engine Marketing Professional Organization, spending on search engine marketing by North American firms in 2008 was estimated at $13.5 billion. Despite the significant role SEA plays in Web retailing, scholarly research on the topic is limited. Prior studies in SEA have focused on search engine auction mechanism design. In contrast, research on the business value of SEA has been limited by the lack of empirical data on search advertising practices. Recent advances in search and retail technologies have created datarich environments that enable new research opportunities at the interface of marketing and information technology. This research uses extensive data from Web retailing and Google-based search advertising and evaluates Web retailers' use of resources, search advertising techniques, and other relevant factors that contribute to business performance across different metrics. The methods used include Data Envelopment Analysis (DEA), data mining, and multivariate statistics. This research contributes to empirical research by analyzing several Web retail firms in different industry sectors and product categories. One of the key findings is that the dynamics of sponsored search advertising vary between multi-channel and Web-only retailers. While the key performance metrics for multi-channel retailers include measures such as online sales, conversion rate (CR), c1ick-through-rate (CTR), and impressions, the key performance metrics for Web-only retailers focus on organic and sponsored ad ranks. These results provide a useful contribution to our organizational level understanding of search engine advertising strategies, both for multi-channel and Web-only retailers. These results also contribute to current knowledge in technology-driven marketing strategies and provide managers with a better understanding of sponsored search advertising and its impact on various performance metrics in Web retailing.