Image search on the web

The storage and retrieval of multimedia has become a requirement for many information systems. This paper presents a comprehensive survey of image search engines, with many clarifying comments. First, we looked at image search engine architecture, followed by the role of the crawler in detecting images. We reviewed the common World Wide Web based systems for image retrieval developed in research institutions and in commercial business. A comparative performance study between the existing engines is also presented.     

Online information search and decision making: Effects of web search stance

A naturalistic online information search exposes individuals to multiple sites and conflicting perspectives. In this study, we evaluated how the holistic stance of a web search toward a product influences purchasing decisions. We recruited 109 participants who completed an initial product choice task regarding bottled water, a brief Internet search, and then a second post-search product choice task. Internet searches were analyzed to identify query terms, site visits, and stance. Results show that query terms influenced the types of sites obtained in a search, which in turn shaped the overall search stance. Participants were more likely to buy bottled water when they visited websites that emphasized environmental, economic, or health benefits for bottled water (i.e., positive stance). Participants who were asked to focus on environmental issues were less likely to buy bottled water unless packaged in recycled plastic.     

Consumer web search behaviour: diagrammatic illustration of wayfinding on the web

External information search behaviour has long been of interest to consumer researchers. Experimental and post hoc survey research methodologies have typically used a large number of variables to record search activity. However, as these are usually considered in aggregate, there is little opportunity for the researcher to overview the search style of a consumer. To date, the diagrammatic illustration of search behaviour has been limited to experimental environments in which the available information was strictly bounded, for example, within databases or when information display boards have been used. This paper, which focuses largely on inter-site world wide web (WWW) search behaviour, discusses web search paradigms and the variables used to capture WWW search. It also provides a conceptual framework for the representation of external information search behaviour in diagrammatic form. The technique offers researchers an opportunity to holistically interpret information search data and search styles. The benefits include the identification of particular search styles, more precise interpretation of web search activity numeric data and the potential application for the training of web users to improve their search effectiveness.     

Collaborative web search: a robustness analysis

Collaborative web search utilises past search histories in a community of like-minded users to improve the quality of search results. Search results that have been selected by community members for past queries are promoted in response to similar queries that occur in the future. The I-SPY system is one example of such a collaborative approach to search. As is the case with all open systems, however, it is difficult to establish the integrity of those who access a system and thus the potential for malicious attack exists. In this paper we investigate the robustness of the I-SPY system to attack. In particular, we consider attack scenarios whereby malicious agents seek to promote particular result pages within a community. In addition, we analyse robustness in the context of community homogeneity, and we show that this key characteristic of communities has implications for system robustness.     

Multiple perspective interactive search: a paradigm for exploratory search and information retrieval on the web

The World Wide Web (WWW) represents the largest and arguably the most complex repository of content at our current state of technological development. Information on the web is represented using a variety of media, with a (current) predominance of text- and images-based data and increasing presence of other media such as video and audio. The complexity and heterogeneity of the information implies that the associated semantics is often user-dependent and emergent. Thus, there is a need to develop novel paradigms for web-based user-data interactions that emphasize user context and interactivity with the goal of facilitating exploration, interpretation, retrieval, and assimilation of information. This article presents a novel presentation-interaction paradigm for exploratory web search which allows simultaneous and semantically correlated presentation of query results from different semantic perspectives. Users can explore the results either using a specific perspective or through a combination of perspectives via highly-intuitive yet powerful interaction operators. In the proposed paradigm, hits obtained from executing a query are first analyzed to determine latent content-based correlations between the pages. Next, the pages are analyzed to extract different types of perceptual and informational cues. This information is used to organize and present the results through an interactive and reflective user interface which supports both exploration and search. Experimental investigations, many of which are conducted in comparative settings, analyze the proposed approach in query-retrieval scenarios involving complex information goals. These results demonstrate the efficacy of the proposed approach and provide important insights for the development of the next-generation of interfaces for web-search.     

On the peninsula phenomenon in web graph and its implications on web search

Web masters usually place certain web pages such as home pages and index pages in front of others. Under such a design, it is necessary to go through some pages to reach the destination pages, which is similar to the scenario of reaching an inner town of a peninsula through other towns at the edge of the peninsula. In this paper, we try to validate that peninsulas are a universal phenomenon in the World-Wide Web, and clarify how this phenomenon can be used to enhance web search and study web connectivity problems. For this purpose, we model the web as a directed graph, and give a proper definition of peninsulas based on this graph. We also present an efficient algorithm to find web peninsulas. Using data collected from the Chinese web by Tianwang search engine, we perform an experiment on the distribution of sizes of peninsulas and their correlations with PageRank values, outdegrees, or indegrees of the ties with other outside vertices. The results show that the peninsula structure on a web graph can greatly expedite the computation of PageRank values; and it can also significantly affect the link extraction capability and information coverage of web crawlers.     

主题搜索引擎中爬虫搜索策略的研究

为了解决传统主题爬虫效率偏低的问题,传统主题爬虫会选择最有价值的链接进行访问,仅简单地计算链接的相关性,却忽视待分析URL之间的相关性关系,致使主题爬虫爬取效率较低。提出一种基于链接模型的相关性判别算法,综合利用有标种子URL和无标的待判别URL实现对无标URL的相关性判别,并推导出迭代初值选取对结果的不敏感性。实验结果表明,与传统的网络爬虫算法相关性判别方法相比,提出的方法效率更高。     

基于REST Web Services的分布式遥感数据检索技术研究

为了更好地解决分布式遥感数据检索的问题,提出了基于REST Web Services的分布式检索实现方法.根据分布式数据检索的需求和遥感数据检索系统的特点,研究了分布式数据检索的实现技术、REST的基本概念、目标与设计原则、主要思想以及实现方式,在此基本上设计了基于REST Web Services分布式遥感数据检索原型系统,并实现了基于REST Web Services分布式遥感数据检索原型系统.     

Improving web search on small screen devices

Small handheld devices—mobile phones, Pocket PCs etc.—are increasingly being used to access the web. Search engines are the most used web services and are an important factor of user support. Search engine providers have begun to offer their services on the small screen. This paper presents a detailed evaluation of the how easy to use such services are in these new contexts. An experiment was carried out to compare users' abilities to complete search tasks using a mobile phone-sized, handheld computer-sized and conventional, desktop interface to the full Google™ index. With all three interfaces, when users succeed in completing a task, they do so quickly (within 2–3 min) and using few interactions with the search engine. When they fail, though, they fail badly. The paper examines the causes of failures in small screen searching and proposes guidelines for improving these interfaces. In addition, we present and discuss novel interaction schemes that put these guidelines into practice.     

基于Web的个性化搜索引擎的研究

分析了传统搜索引擎系统的缺点.设计了一种个性化搜索引擎的体系架构,提出了一种改进的向量空间模型.该模型利用非线性加权的思想来处理特征权值的计算.最后,给出了一种基于改进的向量空间模型的个性化搜索算法,能够针对不同用户提供不同的检索结果.实验结果表明,该结构和算法能够有效地提高搜索引擎的性能,满足用户的个性化需求.     

Implicit: a multi-agent recommendation system for web search

For people with non-ordinary interests, it is hard to search for information on the Internet because search engines are impersonalized and are more focused on “average” individuals with “standard” preferences. In order to improve web search for a community of people with similar but specific interests, we propose to use the implicit knowledge contained in the search behavior of groups of users. We developed a multi-agent recommendation system called Implicit, which supports web search for groups or communities of people. In Implicit, agents observe behavior of their users to learn about the “culture” of the community with specific interests. They facilitate sharing of knowledge about relevant links within the community by means of recommendations. The agents also recommend contacts, i.e., who in the community is the right person to ask for a specific topic. Experimental evaluation shows that Implicit improves the quality of the web search in terms of precision and recall.     

Effects of a metacognitive support device in learning environments

Successful learning is mainly based on metacognitive activities which have to be performed and constantly monitored during learning. Research reveals that many learners have difficulties in performing such metacognitive activities spontaneously, which most probably results in lower learning outcomes. The aim of this study is to experimentally analyse the effects of a metacognitive support device combined with a paper-based prompting scheme. With this support device, students are instructed to activate their repertoire of metacognitive knowledge and skills which should further enhance learning and transfer.     

Scaling up top-K cosine similarity search

Recent years have witnessed an increased interest in computing cosine similarity in many application domains. Most previous studies require the specification of a minimum similarity threshold to perform the cosine similarity computation. However, it is usually difficult for users to provide an appropriate threshold in practice. Instead, in this paper, we propose to search top-K strongly correlated pairs of objects as measured by the cosine similarity. Specifically, we first identify the monotone property of an upper bound of the cosine measure and exploit a diagonal traversal strategy for developing a TOP-DATA algorithm. In addition, we observe that a diagonal traversal strategy usually leads to more I/O costs. Therefore, we develop a max-first traversal strategy and propose a TOP-MATA algorithm. A theoretical analysis shows that TOP-MATA has the advantages of saving the computations for false-positive item pairs and can significantly reduce I/O costs. Finally, experimental results demonstrate the computational efficiencies of both TOP-DATA and TOP-MATA algorithms. Also, we show that TOP-MATA is particularly scalable for large-scale data sets with a large number of items.     

Web designers and web users: Influence of the ergonomic quality of the web site on the information search

Despite rapid growth in the number of web sites, there is still a significant number of ergonomic problems which hinder web users. Many studies focus on analysing cognitive processes and difficulties experienced by web users, but very few are interested in web designers’ difficulties or in comparing their respective activities. Towards this end, the two experimental studies presented in this article compare the strategies developed both by professional web designers and (novice vs. experienced) web users while searching for information on web sites of varying ergonomic quality. More precisely, we investigated whether web designers can effectively use their own strategies as web users when designing web sites. We presented a comparison of novice web users, experienced web users and professional web designers searching behavior and cognitive load when using ergonomic and non-ergonomic web sites. In addition, we asked web designers to predict the strategy used by novice web users. Based on the results obtained in the two experiments, we conclude that web designers are not able to predict strategies of novice users and do not behave like novice users. Consequently, ways for supporting web designers in developing a user-centered activity are necessary, and certain ways are suggested at the end of this article.     

A note on the search for k elements via quantum walk

In this paper we use the quantum walk search scheme by Magniez et al. (2007) [13] to find k solutions of a search problem. We show that the quantum query complexity is at most of order times the number of queries to find one solution.     

Evaluation of service management algorithms in a distributed web search system

The World Wide Web interconnected through the internet today offers numerous specialist topic-oriented or regional search engines and systems in a largely federated heterogeneous environment. Old ones continue to exist and new ones appear in spite of the tremendous progress achieved by their generic Web-wide rival competitors, because they produce better results in their areas of specialisation. However, finding and choosing the best specialised search engines or systems for a particular information need is difficult. This is made even more complicated by the fact that these engines and systems would want to carve out a niche market that generates maximum revenue for themselves. The ADSA (Adaptive Distributed Search and Advertising) Web research project has investigated the problem at some depth and had put forward a search architecture which allows many search engines to be independently owned and controlled, offering advantages over existing centralised architectures. One aspect of the architecture has been to evaluate the service management algorithms that were designed to support competing autonomous systems in a cooperative marketplace. Here we present ADSA economic model and the service management strategies that can lead to maximum revenue generation, by making informative and intelligent decisions on search price adjustments of key quantitative parameters, as well as the results of evaluation experiments and briefly discuss the need for standardised interfaces which are required if this concept is to ease development and implementation of such a marketplace in a large scale.     

Fast exact k nearest neighbors search using an orthogonal search tree

The problem of k nearest neighbors (kNN) is to find the nearest k neighbors for a query point from a given data set. In this paper, a novel fast kNN search method using an orthogonal search tree is proposed. The proposed method creates an orthogonal search tree for a data set using an orthonormal basis evaluated from the data set. To find the kNN for a query point from the data set, projection values of the query point onto orthogonal vectors in the orthonormal basis and a node elimination inequality are applied for pruning unlikely nodes. For a node, which cannot be deleted, a point elimination inequality is further used to reject impossible data points. Experimental results show that the proposed method has good performance on finding kNN for query points and always requires less computation time than available kNN search algorithms, especially for a data set with a big number of data points or a large standard deviation.