Ontology-based specific and exhaustive user profiles for constraint information fusion for multi-agents

Intelligent agents are an advanced technology utilized in Web Intelligence. When searching information from a distributed Web environment, information is retrieved by multi-agents on the client site and fused on the broker site. The current information fusion techniques rely on cooperation of agents to provide statistics. Such techniques are computationally expensive and unrealistic in the real world. In this paper, we introduce a model that uses a world ontology constructed from the Dewey Decimal Classification to acquire user profiles. By search using specific and exhaustive user profiles, information fusion techniques no longer rely on the statistics provided by agents. The model has been successfully evaluated using the large INEX data set simulating the distributed Web environment

Studies in enantioselective catalysis using a novel D-mannitol based titanium trimer

The work presented in this thesis is divided into three parts. This research entails the discovery and development of a novel type of chiral titanium alkoxide, which acts as a Lewis acid for the reduction of prochiral ketones using catecholborane as the stoichiometric reductant. In order to place this methodology in context, the first part is an overview highlighting the usefulness of such transition metal alkoxides in asymmetric organic synthesis. The review mainly revolves around the use of titanium and lanthanide alkoxides. The second part is a discussion of the results obtained. It was discovered that reversible exchange reactions of a series of 3,4-di-O-benzyl-D-mannitol derivatives with titanium(IV) isopropoxide lead to the isolation of a novel trimeric Lewis acid complex which acts as an efficient precursor catalyst for the reduction of a range of prochiral ketones using catecholborane as reducing agent. The behaviour of this Lewis acid as a catalyst in a range of reactions was studied and the mechanism of the borane reduction was shown to involve boron-titanium exchange. The trimeric titanium alkoxide Lewis acid have also been used in a series of other asymmetric reactions and the results were a catalogue of failures. Other ligands derived from D-mannitol have been prepared and used for complexation with both titanium and lanthanum, but the structures of these complexes have so far not been characterised. Testing these unknown complexes on a number of asymmetric reactions proved to be unsuccessful. The third part is an account of the experimental results and procedures employed throughout this work

Automatic domain ontology extraction for context-sensitive opinion mining

Automated analysis of the sentiments presented in online consumer feedbacks can facilitate both organizations’ business strategy development and individual consumers’ comparison shopping. Nevertheless, existing opinion mining methods either adopt a context-free sentiment classification approach or rely on a large number of manually annotated training examples to perform context sensitive sentiment classification. Guided by the design science research methodology, we illustrate the design, development, and evaluation of a novel fuzzy domain ontology based contextsensitive opinion mining system. Our novel ontology extraction mechanism underpinned by a variant of Kullback-Leibler divergence can automatically acquire contextual sentiment knowledge across various product domains to improve the sentiment analysis processes. Evaluated based on a benchmark dataset and real consumer reviews collected from Amazon.com, our system shows remarkable performance improvement over the context-free baseline

Ontology-based specific and exhaustive user profiles for constraint information fusion for multi-agents

Intelligent agents are an advanced technology utilized in Web Intelligence. When searching information from a distributed Web environment, information is retrieved by multi-agents on the client site and fused on the broker site. The current information fusion techniques rely on cooperation of agents to provide statistics. Such techniques are computationally expensive and unrealistic in the real world. In this paper, we introduce a model that uses a world ontology constructed from the Dewey Decimal Classification to acquire user profiles. By search using specific and exhaustive user profiles, information fusion techniques no longer rely on the statistics provided by agents. The model has been successfully evaluated using the large INEX data set simulating the distributed Web environment

THE DESIGN OF A NETWORK-BASED MODEL FOR BUSINESS PERFORMANCE PREDICTION

While much research work has been devoted to analysis and prediction of individuals’ behavior in social networks, very few studies about the analysis of business networks are conducted. Empowered by recent research on automated mining of business networks, this paper illustrates the design of a novel business network-based model called Energy Cascading Model (ECM) for the analysis and prediction of business performance using the proxies of stock prices. More specifically, the proposed prediction model takes into account both influential business relationships and twitter sentiments of firms to infer their stock price movements. Our empirical experiments based on a publicly available financial corpus and social media postings reveal that the proposed ECM model is effective for the prediction of directional stock price movements. The business implication of our research is that business managers can apply our design artifacts to more effectively analyze and predict the potential business performance of targeted firms

Using Information Filtering in Web Data Mining Process

Web service-oriented Grid is becoming a standard for achieving loosely coupled distributed computing. Grid services could easily be specified with web-service based interfaces. In this paper we first envisage a realistic Grid market with players such as end-users, brokers and service providers participating co-operatively with an aim to meet requirements and earn profit. End-users wish to use functionality of Grid services by paying the minimum possible price or price confined within a specified budget, brokers aim to maximise profit whilst establishing a SLA (Service Level Agreement) and satisfying end-user needs and at the same time resisting the volatility of service execution time and availability. Service providers aim to develop price models based on end-user or broker demands that will maximise their profit. In this paper we focus on developing stochastic approaches to end-user workflow scheduling that provides QoS guarantees by establishing a SLA. We also develop a novel 2-stage stochastic programming technique that aims at establishing a SLA with end-users regarding satisfying their workflow QoS requirements. We develop a scheduling (workload allocation) technique based on linear programming that embeds the negotiated workflow QoS into the program and model Grid services as generalised queues. This technique is shown to outperform existing scheduling techniques that don't rely on real-time performance information

Information Granulation for the Design of Granular Information Retrieval Systems

With the explosive growth of the amount of information stored on computer networks such as the Internet, it is increasingly more difficult for information seekers to retrieve relevant information. Traditional document ranking functions employed by Internet search engines can be enhanced to improve the effectiveness of information retrieval (IR). This paper illustrates the design and development of a granular IR system to facilitate domain specific search. In particular, a novel computational model is designed to rank documents according the searchers’ specific granularity requirements. The initial experiments confirm that our granular IR system outperforms a classical vector-based IR system. In addition, user-based evaluations also demonstrate that our granular IR system is effective when compared with a well-known Internet search engine. Our research work opens the door to the design and development of the next generation of Internet search engines to alleviate the problem of information overload

Rules-based international order and US Indo-Pacific strategy: what does it mean for China's BRI?

The third decade of the 21st century has witnessed more tensions, instabilities, and new alliances in the Indo-Pacific/Asia-Pacific region due to intensifying rivalry and strategic competition between the US Indo-Pacific Strategy (IPS) and China's Belt and Road Initiative (BRI), two grand strategies of the US and China respectively. This article aims to assess the Rules-Based International Order (RBIO) and comprehend Biden's IPS, particularly exploring how the Indo-Pacific Economic Framework (IPEF) may impact China's BRI. This paper argues that RBIO is debatable and not universal. It is also argued that while the IPEF unveiled by President Biden represents a strategically important step forward, a long-term US genuine commitment to its implementation to counter China's BRI is essential. The methodology of this research is primarily based on secondary literature and official documents. This study concludes that although China is reluctant to pay too much attention to the US IPEF in its official statements, China is concerned about this economic initiative. The paper also concludes that because of the intense US-China rivalry, new alliances will emerge in the region leading to a new cold war or new world order