Web Intelligence Techniques Research Articles

Bayesian Deep Learning Enabled Sentiment Analysis on Web Intelligence Applications

In recent times, web intelligence (WI) has become a hot research topic, which utilizes Artificial Intelligence (AI) and advanced information technologies on the Web and Internet. The users post reviews on social media and are employed for sentiment analysis (SA), which acts as feedback to business people and government. Proper SA on the reviews helps to enhance the quality of the services and products, however, web intelligence techniques are needed to raise the company profit and user fulfillment. With this motivation, this article introduces a new modified pigeon inspired optimization based feature selection (MPIO-FS) with Bayesian deep learning (BDL), named MPIO-BDL model for SA on WI applications. The presented MPIO-BDL model initially involved preprocessing and feature extraction take place using Term Frequency—Inverse Document Frequency (TF-IDF) technique to derive a useful set of information from the user reviews. Besides, the MPIO-FS model is applied for the selection of optimal feature subsets, which helps to enhance classification accuracy and reduce computation complexity. Moreover, the BDL model is employed to allocate the proper class labels of the applied user review data. A comprehensive experimental results analysis highlighted the improved classification efficiency of the presented model.

Who is answering whom? Finding “Reply-To” relations in group chats with deep bidirectional LSTM networks

Social networks facilitate communication among Internet users while generating large volumes of online short-text conversations every day. This leads to a huge number of free-style asynchronous conversations where multiple users are involved and multiple topics are discussed at the same time in the same place, e.g., an instant group chat in WeChat. Here emerges an interesting problem: as a result of a large number of users and topics, the conversation structure may get into a mess, which often interferes with the acquisition of messages users are interested in. For example, when a user enters a conversation, (s)he usually does not want to read all the historical messages, but just hope to get the messages that are the most relevant to some messages (s)he cares about. Therefore, it is an essential task to understand the logical correlations among messages, which benefits text mining, natural language processing, and web intelligence techniques. In this paper, we focus on “reply-to” relations, such as QA The other two versions are end-to-end models, which are based on the word level and the sentence level, respectively. Finally, experimental results conducted on two real-world group chat data sets demonstrate the effectiveness of the proposed model.

A Model for Web-Intelligence Index to Evaluate the Web Intelligence Capacity of Government Web Sites of Sri Lanka

Web intelligence can be considered as a subset of Artificial Intelligence. It uses existing data in web to produce new data, knowledge and wisdom to support decision making and new predictions for web users. Artificial Intelligence is ever changing and evolving field of computer science and it is extensively used in wide array of web based business applications. Although it is used substantially in web based systems in developed countries, it is not examined whether it is being substantially used in Sri Lanka. Every Sri Lankan citizen depends on Public Service more or less throughout his/ her life time and at least more than 3 times: at birth, marriage and death. So providing most of these services to its citizen, Sri Lankan Government uses more or less of its country web portal. This paper presents a model to evaluate web intelligence capability based on weight to key functionalities with respect to web intelligence. The government websites were checked by the proposed criteria to show the potential of using web intelligent technology to provide website based services. The result indicates that the use of web intelligence techniques openly and publicly to provide web based services through government web portal to its citizens is not satisfactory. It also indicates that lack of using the technologies pertaining to web intelligence in the public service web hinders the most of the advantages that citizen and government can gain from such technological involvement.

Web intelligence analyses of digital libraries

Purpose – The purpose of this paper is to explore the use of LexiURL as a Web intelligence tool for collecting and analysing links to digital libraries, focusing specifically on the National electronic Library for Health (NeLH).Design/methodology/approach – The Web intelligence techniques in this study are a combination of link analysis (web structure mining), web server log file analysis (web usage mining), and text analysis (web content mining), utilizing the power of commercial search engines and drawing upon the information science fields of bibliometrics and webometrics. LexiURL is a computer program designed to calculate summary statistics for lists of links or URLs. Its output is a series of standard reports, for example listing and counting all of the different domain names in the data.Findings – Link data, when analysed together with user transaction log files (i.e. Web referring domains) can provide insights into who is using a digital library and when, and who could be using the digital library...

ON KNOWLEDGE GRID AND GRID INTELLIGENCE: A SURVEY

The next generation Web Intelligence (WI) aims at enabling users to go beyond the existing online information search and knowledge queries functionalities and to gain, from the Web, practical wisdom for problem solving. To support such a Wisdom Web, we envision that a grid‐like computing infrastructure with intelligent service agencies is needed, where these agencies can interact, self‐organize, learn, and evolve their course of actions, identities, and interrelationships for new knowledge creation, as well as scientific and social evolution. In this paper, we first provide an overview of recent development in WI and Semantic/Knowledge Grid. Then, the fundamental capabilities of the Wisdom Web as well as the conceptual architecture of an intelligent Grid for supporting it are described. Technical challenges for realizing Grid Intelligence are highlighted and the recent advancements in related research areas are reviewed.