Measuring task-specific perceptions of the world wide web

This paper describes the development of multi-item scales for measuring user perceptions of the ease-of-use and usefulness of the Web (hereafter web), incorporating a system task focus into the scales dimensional structure (e.g. how easy or useful the web is for information search, communication and or purchasing). The items are tested on 2077 web users recruited using a web survey, revealing four factors for each scale. Perceived ease-of-web use consists of learning, search and find, transaction and communication ease, and perceived web usefulness consists of communication, purchase, information search and acquisition, and access to quality products and information. A regression analysis on web usage frequency shows how easy users find it to learn how to use the web and how useful the web is for purchasing are the best predictors of how frequently they will use the web. These results highlight the importance of training users how to effectively use hypermedia-based systems like the web, and the design of systems that are easy to navigate and that provide advanced functionality for transactional activity.     

Using extended web technologies to develop Bluetooth multi-platform mobile applications for interact with smart things

Nowadays the classic web paradigms are being subjected to changes; every day millions of users around the world use their Smartphones to access web applications from anywhere. The World Wide Web it is one of the biggest repositories of information in the world, and that information is stored in internet servers and repositories, but today in the real world there are many other information sources such as electronic devices with communication capabilities: smart appliances and sensor networks. The Smartphones are equipped with communication hardware elements like the Bluetooth module, which allows the Smartphone to exchange information with nearby electronic devices. Every day more and more mobile applications are being developed for native platforms that use Bluetooth’s communication module to send and receive information from different sources. Native mobile applications use the specific platform’s APIs to manage the Bluetooth communication actions (send and receive information, search for devices, etc.), however, web applications do not have technical capabilities to manage the Smartphone’s Bluetooth communication module and thereof cannot use that kind of information. The main objective of this research work is to design a novel framework that allows classic web applications to use information from nearby electronic devices. The proposed framework must be easy to use and able to be integrated with common web technologies. Developers can use this framework to include new information sources and data exchange procedures in an easy way. The new type of information can be merged with the web to develop or improve algorithms and web applications.     

Using social networks to distort users’ profiles generated by web search engines

The Internet is one of the most important sources of knowledge in the present time. It offers a huge volume of information which grows dramatically every day. Web search engines (e.g. Google, Yahoo…) are widely used to find specific data among that information. However, these useful tools also represent a privacy threat for the users: the web search engines profile them by storing and analyzing all the searches that they have previously submitted. To address this privacy threat, current solutions propose new mechanisms that introduce a high cost in terms of computation and communication. In this paper, we propose a new scheme designed to protect the privacy of the users from a web search engine that tries to profile them. Our system uses social networks to provide a distorted user profile to the web search engine. The proposed protocol submits standard queries to the web search engine; thus it does not require any change in the server side. In addition to that, this scheme does not require the server to collaborate with the users. Our protocol improves the existing solutions in terms of query delay. Besides, the distorted profiles still allow the users to get a proper service from the web search engines.     

Web accessibility awareness in search engine results

The enormous amount of information available on the Internet requires the use of search engines in order to find specific information. As far as web accessibility is concerned, search engines contain two kinds of barriers: on the one hand, the interfaces for making queries and accessing results are not always accessible; on the other hand, web accessibility is not taken into account in information retrieval (IR) processes. Consequently, in addition to interface problems, accessing the items in the list of results tends to be an unsatisfactory experience for people with disabilities. Some groups of users cannot take advantage of the services provided by search engines, as the results are not useful due to their accessibility restrictions. The goal of this paper is to propose the integration of web accessibility measurement into information retrieval processes. Firstly, quantitative accessibility metrics are defined in order to accurately measure the accessibility level of web pages. Secondly, a model to integrate these metrics within IR processes is proposed. Finally, a prototype search engine which re-ranks results according to their accessibility level based on the proposed model is described.     

Using semantic techniques to access web data

Nowadays, people frequently use different keyword-based web search engines to find the information they need on the web. However, many words are polysemous and, when these words are used to query a search engine, its output usually includes links to web pages referring to their different meanings. Besides, results with different meanings are mixed up, which makes the task of finding the relevant information difficult for the users, especially if the user-intended meanings behind the input keywords are not among the most popular on the web.     

Perceptions of web knowledge and usability: When sex and experience matter

Web users are now a mixture of consumer and web designer. As such, the context within which we are socialized about the web – as both male and female users – moderates the relationship between what we think we know about it and its usability to complete tasks. With online survey data from 2077 web users, we empirically examine the relationship between user perceptions of web knowledge (our confidence in what we think we know) and user beliefs about usability of the web (how easy and useful we believe it to be). We include a user’s sex and their website design experience as important moderators on this relationship. Results show a positive relationship between perceived web knowledge and web usability, and under the context of website design experience, more value is placed on the utility of the web, rather than on its ease of use. This moderation effect is stronger for female than it is for male web users. In summary, users with more confidence in their knowledge are more oriented towards the utility of the web than how easy it is to harvest that utility. Our work contributes to an understanding of the influence of the usage context within which the knowledge and beliefs of male and female users are socialized about web technology.     

A trustworthy QoS-based collaborative filtering approach for web service discovery

Many network services which process a large quantity of data and knowledge are available in the distributed network environment, and provide applications to users based on Service-Oriented Architecture (SOA) and Web services technology. Therefore, a useful web service discovery approach for data and knowledge discovery process in the complex network environment is a very significant issue. Using the traditional keyword-based search method, users find it difficult to choose the best web services from those with similar functionalities. In addition, in an untrustworthy real world environment, the QoS-based service discovery approach cannot verify the correctness of the web services’ Quality of Service (QoS) values, since such values guaranteed by a service provider are different from the real ones. This work proposes a trustworthy two-phase web service discovery mechanism based on QoS and collaborative filtering, which discovers and recommends the needed web services effectively for users in the distributed environment, and also solves the problem of services with incorrect QoS information. In the experiment, the theoretical analysis and simulation experiment results show that the proposed method can accurately recommend the needed services to users, and improve the recommendation quality.     

Information structure and practice as facilitators of deaf users' navigation in textual websites

Deaf users might find it difficult to navigate through websites with textual content which, for many of them, constitutes the written representation of a non-native oral language. With the aim of testing how the information structure could compensate for this difficulty, 27 prelingual deaf users of sign language were asked to search a set of headlines in a web newspaper where information structure and practice were manipulated. While practice did not affect deep structures (web content distributed through four layers of nodes), wide structures (web content concentrated in two layers) did facilitate users' performance in the last trial block and compromised it in the first trial block. It is argued that wide structures generate a textual information overload for deaf users, which decreases with practice. Thus, wide structures seem preferable for websites requiring frequent use, rather than for those intended for occasional interaction.     

Supporting social navigation on the World Wide Web

This paper discusses a navigation behavior on Internet information services, in particular the World Wide Web, which is characterized by pointing out information using various communication tools. We call this behaviorsocial navigationas it is based on communication and interaction with other users, be it through email, or any other means of communication. Social navigation phenomena are quite common although most current tools (like web browsers or email clients) offer very little support for it. We describe why social navigation is useful and how it can be supported better in future systems. We further describe two prototype systems that, although originally not designed explicitly as tools for social navigation, provide features that are typical for social navigation systems. One of these systems, the Juggler system, is a combination of a textual virtual environment and a web client. The other system is a prototype of a web-hotlist organizer, called Vortex. We use both systems to describe fundamental principles of social navigation systems.     

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.     

一种WWW搜索引擎的设计与实现

随着Internet在我国的迅速发展和WWW信息的不断增长,迫切需要开发中英文兼容的WWW搜索引擎来获得所需的信息。该文在分析WWW搜索引擎主要功能模块:信息采集模块、信息预处理模块和信息查询模块的基础上,提出采用人工智能搜索算法来遍历网页,对中英文网页进行自动的索引,并用向量空间的表示方法来表示网页内容和用户输入的查询表达式。实践证明,使用该搜索引擎,可以快速准确地搜索到用户所需的信息。     

一种改进的页面相似性度量方法

Web 信息检索是指从大量Web 文档集合中找到与给定的查询请求相关的、恰当数目的文档子集。为了更准确地找到相似文档,借助于两个页面的单词覆盖程度,提出一种改进的Web 页面检索度量方法,并在KNN分类实验中得到验证。     

基于摘要的web内容挖掘研究

Internet是一个巨大的,分步广泛的,动态性强的全球信息服务中心,人们想在它上面找到想要的相关信息是很困难的,一般用户通过给搜索引擎提供简短的关键词来检索信息,但是通过搜索引擎返回的相关结果太多,这使得处理相关结果太耗时,本文提出了一种语义虚拟文档(SVD)来表示web文档,在此基础上实现了凝聚层次聚类算法,以自动聚类内容相似的web文档。结果:一方面使网络用户增强了相关结果的判断处理,同时使用户快速、高效的从Internet上发现想要的信息,另一方面返回的结果在知识表示上增强了web内容挖掘。     

智能语义搜索引擎的探究

现有搜索引擎系统在响应用户搜索请求的过程中,往往根据分词后的查询关键词在文档中出现的次数来匹配文档内容,这种仅仅根据词频来确定关键词和文档之间相关度的方法往往缺乏一定的准确性,常常导致搜索引擎的网页结果列表并不是用户真正想要的内容,这给用户的检索过程带来极大不便,也是搜索引擎"查准率"得不到彻底改善的主要原因。该文通过构建对象语义库来存储和管理各种对象集,从而实现用户基于对象的检索过程,以提高搜索引擎查询的准确率。     

结构化网页的管理方法

近些年对internet的使用提供了获取大量信息的方法。但是，在单个网页中或者多个网页间缺少信息结构，成为获取网络数据的障碍。因此为了有效地搜索网络信息，迫切需要结构化网页有效的管理方法。该文提出的结构化网页的管理方法基于以下两个方面：第一步把HTML转化为XML，第二步建立导航层次结构。同时也学习如何用结构化的网页管理方法进行有效的数据查询，用户可以按照网站的导航层次浏览整个网站，包括互联的网页或者内部的网页，并且可以搜索感兴趣的信息。     

Intelligent system for visual web content analytics: A new approach and case study

The accuracy of searches for visual data elements, as well as other types of information, depends on the terms used by the user in the input query to retrieve the relevant results and to reduce the irrelevant ones. Most of the results that are returned are relevant to the query terms, but not to their meaning. For example, certain types of web contents hold hidden information that traditional search engines are unable to retrieve. Searching for the mathematical construct of 1/x using Google will not result in the retrieval of the documents that contain the mathematically equivalent expressions (i.e. x^?1). Because conventional search engines fall short of providing math-search capabilities. One of these capabilities is the ability of these search engines to detect the mathematical equivalence between users’ quires and math contents. In addition, users sometimes need to use slang terms, either to retrieve slang-based visual data (e.g. social media content) or because they do not know how to write using classical form. To solve such a problem, this paper proposed an AI-based system for analysing multilingual slang web contents so as to allow a user to retrieve web slang contents that are relevant to the user’s query. The proposed system presents an approach for visual data analytics, and it also enables users to analyse hundreds of potential search results/web pages by starting an informed friendly dialogue and presenting innovative answers.     

Understanding novelty: how task structure and tool familiarity moderate performance

Consumers and corporate end users are regularly faced with the challenge of adapting to new technology tools and their user interfaces. Understanding the role of user experience in using these new interfaces is an important aspect of assessing and planning for how new innovations are received. Through a controlled laboratory experiment in the information retrieval domain, we find that the effect of task (web search) familiarity on performance depends on the task structure (open-ended versus closed-ended) and the degree of tool familiarity (a traditional textual list versus a novel graphical interface for presenting web search results). Our results show that task experience has a positive effect on performance when the task structure is closed-ended and the interface is familiar, and a negative effect when the task structure is open-ended and the interface is unfamiliar. This study not only adds to the literature on user experience in the context of IT use, but also has practical implications for the testing and adoption of new technologies, indicating that novices may be better, or at least an important group, for testing truly novel tools and their interfaces.     

Intranet搜索引擎设计与实现

随着企业内部网络应用的深入,Intranet内部的信息资源越来越庞大,怎样为这些数据信息构建索引是我们面If缶的主要任务,而全文检索的产生解决了这一问题。目前越来越多的中小企业采用Linux系统作为Web平台,并且利用检索系统来管理内部繁多的文本和HTML文件。文章对www搜索引擎的全文检索及其相关技术进行了分析和讨论,实现了一个基于Linux环境的Intranet搜索引擎LISE（Linux Intranet Search Engine）。LISE利用了基于词表的索引方法,为用户提供了更加准确的信息,能满足多种中小企业用户的需求。     

基于知识的网页检索工具

随着因特网在全球范围的广泛使用,越来越多的人们借助于因特网从事科研和商务活动,而网页检索工具成了人们必不可少的软件工具．然而,目前流行的检索工具大多基于关键字查询,常常出现信息过载或有用信息丢失等现象．造成这一原因主要有两方面：用户提交的查询不能很好地表达他的目的;查询的结果没有建立有效的索引机制,引导人们快速找到有用信息。为此我们提出一种基于知识的网页检索工具（ＫＷＳＥ）,它是在已有的检索工具的     

知识图谱研究综述

随着信息化社会的来临,各种互联网技术应运而生,数字信息已然成为当今社会中商家必争的宝贵财富资源。众多数字信息中,怎样帮助用户精准筛选出有效信息是当前搜索引擎所面临的巨大挑战。传统的互联网搜索仅仅是基于本文的链接,搜索时仅单纯的给出包含搜索词的网页,让用户去网页中寻找答案,这种检索方法耗时耗力,还不能准确给出用户想要的答案。由此谷歌率先提出以知识图谱(Knowledge Graph)为技术基础的的搜索引擎,这是搜索引擎界的一次重大变革。它以图的形式表现客观世界中的概念和实体及其之间关系,现如今广泛应用于语义搜索、智能问答、决策支持等智能服务领域。本文针对什么是知识图谱、如何表示构建知识图谱及知识图谱的主要应用作了详细阐述,希望更多的读者可以了解知识图谱及其对人工智能发展的巨大贡献。