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Marketing Conference. Also Include Department All. Show All Last Month Many tasks once performed by humans are now carried out by autonomous artificial intelligence systems. An important aspect of such systems is their accountability, that is, how their decisions and behaviours can be recorded, scrutinised and, if necessary, revised. This project will investigate how agents operating as part of a group should learn behaviours that benefit the group as a whole.
These behaviours are commonly referred to as norms, and describe obligations, permissions and prohibitions on actions in specific contexts. This project will investigate how the decisions made by an AI system operating as part of a group can be explained. Therefore, it is necessary that CBSD should be driven by stakeholder's requirements. CBSD requirements are collected as high level needs, and are then modelled by identifying the importance of each need.
Each need is identified as mandatory, important, essential or optional. This project is to investigate into having a systematic process of refining these requirements by specifying candidate components.
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You may wonder when we type the question "What is the weather today in Melbourne? A QA system converts a user's query into a sequence of key words, conducts web search using the keywords, and identifies the most proper text segment as the answer to the query. A QA system contains a number of components. The first component is Query Expansion. The research project is to analyse the query being entered by the user, to expand it by adding synonyms, to identify the key words within the query, and finally to decide the precise meaning of each key word.
Word Sense Disambiguation techniques will be applied to the research. The World Wide Web contains a huge number of documents which express opinions, containing comments, feedback, critiques, reviews and blogs, etc.
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These documents provide valuable information which can help people with their decision making. For example, product reviews can help enterprises promote their products; comments on a policy can help politicians clarify their political strategy; event critiques can help the involved parties reflect on their activities, etc.
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However, the number of these types of documents is huge, so it is impossible for humans to read and analyse all of them. Thus, automatically analyzing opinions expressed on various web platforms is increasingly important for effective decision making.
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The task of developing such a technique is sentiment analysis or opinion mining. In this project, we attempt to analyse the sentiment orientation of a sample by identifying the connectives and phrases in its text. As a result, the keyword which expresses the sentiment orientation of the author can be identified. The method is to be compounded with classical analysis methods machine learning based or clustering based to achieve a higher accuracy. The purpose of the research is to establish a new scheme in knowledge representation — Natural Language Independent Knowledge Representation.
A concept can be implemented as a class in JAVA programming language. The class hierarchy can be established through the inheritance relationship.
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Attributes in the class define the relations between concepts. The scheme can be applied to Natural Language Processing, Sentiment Analysis and Question-Answering Systems to serve as a tool for identifying the precise meaning of a word, and consequently to achieve Word Sense Disambiguation.
Surveys, or questionnaires, are a very common means to obtained information in scientific and social investigations. Typically, the data are entered into a number of data files e.
As the work progressed, to test some hypotheses, or to perform some exploratory analysis, new data files often had to be prepared. This approach is very time-consuming and error-prone. In fact, this project serves two related purposes: 1 To systematically ensure that we can store all the relevant data and maximize their use for statistical analysis, and 2 To construct an ontology of the related field to improve the concepts and their relationships in that field. SBVR Semantics Business Vocabulary and Rules is the comprehensive standard for defining the vocabulary and rules of application domains.
That is, the aim of SBVR is to capture and represent all the business concepts vocabulary and all the business rules. The importance of business rules is that they drive the business activities and they govern the way the business software system behaves.
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In other words, the concepts and rules captured by SBVR represent the business knowledge required to understand the business and to build software systems to support the business. The aim of the thesis is to study the SBVR standard in depth, to survey the works that have been published since the release of the Standard, and to critically evaluate the applicability of SBVR to practical information system development. Business rules are the most important factor that determines the structure and behaviour of an information system.
This is a very important task for building business-rule-driven information system. Typically, the process for building such a system starts with building an SBVR model and then translates that model into a UML model, which is more suitable for practical implementation. The aim of web services is to make data resources available over the Internet to applications programs written in any language. RESTful Web services have now been recognized as generally the most useful methods to provide data-services for web and mobile application development. The aim of the thesis is to study the concept of RESTful web services in depth and to construct a catalogue of patterns for designing data-intensive web services.
The aim of the catalogue is to act as a guide for practical design of web services for application development.