User feedback based enhancement in web search quality

Of late, there has been a paradigm shift in web searching from the content based searching to the connectivity based or more commonly known as hyperlink based (or simply link based) searching. But, both the content based approach as well as the link based approach are objective ones, which are totally dependent on the effectiveness of their “feature extraction” mechanisms, with no apparent consideration to the preference of the searcher. In this work, a “user satisfaction” guided web search procedure is proposed. We calculate the importance weight of each document viewed by the user based on the feedback vector obtained from his actions. This document weight is then used to update the index database in such a way that the documents being consistently preferred go up the ranking, while the ones being neglected go down. Our simulation results show a steady rise in the satisfaction levels of the modeled users as more and more learning goes into our system. We also propose a couple of novel additions to the web search querying techniques.     

A novel visualization model for web search results

This paper presents an interactive visualization system, named WebSearchViz, for visualizing the Web search results and acilitating users' navigation and exploration. The metaphor in our model is the solar system with its planets and asteroids revolving around the sun. Location, color, movement, and spatial distance of objects in the visual space are used to represent the semantic relationships between a query and relevant Web pages. Especially, the movement of objects and their speeds add a new dimension to the visual space, illustrating the degree of relevance among a query and Web search results in the context of users' subjects of interest. By interacting with the visual space, users are able to observe the semantic relevance between a query and a resulting Web page with respect to their subjects of interest, context information, or concern. Users' subjects of interest can be dynamically changed, redefined, added, or deleted from the visual space.     

Assisting web search using query suggestion based on word similarity measure and query modification patterns

One of the useful tools offered by existing web search engines is query suggestion (QS), which assists users in formulating keyword queries by suggesting keywords that are unfamiliar to users, offering alternative queries that deviate from the original ones, and even correcting spelling errors. The design goal of QS is to enrich the web search experience of users and avoid the frustrating process of choosing controlled keywords to specify their special information needs, which releases their burden on creating web queries. Unfortunately, the algorithms or design methodologies of the QS module developed by Google, the most popular web search engine these days, is not made publicly available, which means that they cannot be duplicated by software developers to build the tool for specifically-design software systems for enterprise search, desktop search, or vertical search, to name a few. Keyword suggested by Yahoo! and Bing, another two well-known web search engines, however, are mostly popular currently-searched words, which might not meet the specific information needs of the users. These problems can be solved by WebQS, our proposed web QS approach, which provides the same mechanism offered by Google, Yahoo!, and Bing to support users in formulating keyword queries that improve the precision and recall of search results. WebQS relies on frequency of occurrence, keyword similarity measures, and modification patterns of queries in user query logs, which capture information on millions of searches conducted by millions of users, to suggest useful queries/query keywords during the user query construction process and achieve the design goal of QS. Experimental results show that WebQS performs as well as Yahoo! and Bing in terms of effectiveness and efficiency and is comparable to Google in terms of query suggestion time.     

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.     

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.     

The HWS hybrid web search

The widespread availability of machine understandable information on the Semantic Web offers some opportunities to improve traditional search. In this paper, we propose a hybrid web search architecture-HWS, which combines text search with semantic search to improve precision and recall. The components in HWS are described in detail, including several novel algorithms proposed to support the hybrid web search.     

A similarity measure for the negotiation in web services

This paper presents a new negotiation approach integrating a similarity-based metric to measure the client’s satisfaction level by quantifying the correspondence between the features required by the client and the ones proposed by the service. This negotiation process is integrated within an adaptation platform for multimedia presentations supporting different types of terminals. The negotiation and adaptation processes are based on the management of user’s and service’s profiles. We also propose an extension of the SIP protocol to ensure the communication between the client and the server by defining new functionalities.     

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。     

Survey on mining subjective data on the web

In the past years we have witnessed Sentiment Analysis and Opinion Mining becoming increasingly popular topics in Information Retrieval and Web data analysis. With the rapid growth of the user-generated content represented in blogs, wikis and Web forums, such an analysis became a useful tool for mining the Web, since it allowed us to capture sentiments and opinions at a large scale. Opinion retrieval has established itself as an important part of search engines. Ratings, opinion trends and representative opinions enrich the search experience of users when combined with traditional document retrieval, by revealing more insights about a subject. Opinion aggregation over product reviews can be very useful for product marketing and positioning, exposing the customers’ attitude towards a product and its features along different dimensions, such as time, geographical location, and experience. Tracking how opinions or discussions evolve over time can help us identify interesting trends and patterns and better understand the ways that information is propagated in the Internet. In this study, we review the development of Sentiment Analysis and Opinion Mining during the last years, and also discuss the evolution of a relatively new research direction, namely, Contradiction Analysis. We give an overview of the proposed methods and recent advances in these areas, and we try to layout the future research directions in the field.     

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.     

基于主观逻辑的Web服务信任模型

在分析了传统主观信任评估模型存在问题的基础上提出了相应的改进方法,将改进后的信任评估模型方法应用到Web服务环境中,从而使Web服务环境中的实体信任度随着交易次数的增加能够自动更新.最后,通过模拟试验表明改进后的主观信任评估模型能更好的反应Web服务环境中实体信任度的变化.     

一种快速网页检索结果聚类策略

在网页聚类中,HAC（Hierarchical Agglomerative Clustering）算法和K-means算法都是经常用到的。但它们都有各自的不足。提出一种两阶段聚类方法。第一阶段利用HAC聚类算法对网络检索结果的标题进行聚类,第二阶段以第一阶段结果作为初始中心用K-means算法聚类标题和摘要取得比较合理的聚类结果。由于标题一般都比较短,可以大大减少HAC算法的运行时间。这样既满足网络检索对时间的要求又可以得到较好的聚类结果。     

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.     

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.     

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.     

基于Silverlight网页游戏的寻径优化算法

为了解决A*路径搜索算法在Silverlight网页游戏中的搜索费时和路径曲折等问题,在结合光线跨越算法和引入父结点指针的二叉堆存储开启列表的A*算法的基础上,提出了一种基于Silverlight网页游戏的寻径优化算法。该算法在现有研究的基础上使用光线跨越算法减小A*算法搜索规模,同时将动态关键点技术与光线跨越算法结合来优化算法返回的路径。将该算法在游戏所使用的网格地图中进行实验,实验结果表明,该算法能够有效地根据系统设定的通行条件寻找出一条最优的实际可行的路径,同时缩短寻路的时间消耗和所寻的路径长度,提高游戏的可玩性。     

Clustering web search results using fuzzy ants

Algorithms for clustering Web search results have to be efficient and robust. Furthermore they must be able to cluster a data set without using any kind of a priori information, such as the required number of clusters. Clustering algorithms inspired by the behavior of real ants generally meet these requirements. In this article we propose a novel approach to ant‐based clustering, based on fuzzy logic. We show that it improves existing approaches and illustrates how our algorithm can be applied to the problem of Web search results clustering. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 455–474, 2007.