Submodular memetic approximation for multiobjective parallel test paper generation

Parallel test paper generation is a biobjective distributed resource optimization problem, which aims to generate multiple similarly optimal test papers automatically according to multiple user-specified assessment criteria. Generating high-quality parallel test papers is challenging due to its NP-hardness in both of the collective objective functions. In this paper, we propose a submodular memetic approximation algorithm for solving this problem. The proposed algorithm is an adaptive memetic algorithm (MA), which exploits the submodular property of the collective objective functions to design greedy-based approximation algorithms for enhancing steps of the multiobjective MA. Synergizing the intensification of submodular local search mechanism with the diversification of the population-based submodular crossover operator, our algorithm can jointly optimize the total quality maximization objective and the fairness quality maximization objective. Our MA can achieve provable near-optimal solutions in a huge search space of large datasets in efficient polynomial runtime. Performance results on various datasets have shown that our algorithm has drastically outperformed the current techniques in terms of paper quality and runtime efficiency

Using CSP to model the synchronisation process of variable length codes

Variable length codes (VLC) have found widespread use for efficient encoding of symbols with unequal probabilities in many practical situations. However, bit errors can cause a loss of decoder synchronism that often leads to error propagation. Recent advances in the development of VLC that limit the effect of error propagation, such as reversible VLC and self-synchronising VLC, contribute further to their popularity. However, it is still important to model the performance of various VLC code sets so that comparisons can be made between different coding schemes and for different applications. Communicating sequential processes (CSP) is a well-established formal description technique that allows one to analyse the behaviour of concurrently evolving processes. It has been successfully applied to industrial-scale problems. The paper describes how CSP can be applied to the modelling of the resync process of VLC. This approach offers three main advantages. First, a complete model comprises processes and events as basic building blocks, making this approach highly scalable. Second, different semantic models provide different level of abstraction. Third, tools are available for automatic generation of sync sequences, which also provide a measure of sync performance. This facilitates comparisons of different VLC schemes in addition to code sets obtained using a given coding scheme

An end-to-end solution for Internet lecture delivery

No abstract available

Associative Feature Selection for Text mining

No abstract available

E-Business project management: man- aging the planning process

This paper studies the strategic planning process of an electronic business project. In today’s fast growing demand of electronic transactions, with more people accessing the internet worldwide, online shopping becomes an increasingly profitable but risky business. Selling online becomes a very competitive business and time is a critical factor in launching a web site for business. This paper identifies how risks can be minimized by proper planning and how planning is implemented. It also describes how to detect any changes in the marketplace so that effective measures can be made to avoid dropping out from competition. The emphasis is on the planning tactics, particularly in ensuring accurate tracking that is specific to the e-business start up process

A web usage lattice based mining approach for intelligent web personalization

With the explosive growth of information available on the World Wide Web, it has become much more difficult to access relevant information from the Web. One possible approach to solve this problem is web personalization. In this paper, we propose a novel WUL (Web Usage Lattice) based mining approach for mining association access pattern rules for personalized web recommendations. The proposed approach aims to mine a reduced set of effective association pattern rules for enhancing the online performance of web recommendations. We have incorporated the proposed approach into a personalized web recommender system known as AWARS. The performance of the proposed approach is evaluated based on the efficiency and the quality. In the efficiency evaluation, we measure the number of generated rules and the runtime for online recommendations. In the quality evaluation, we measure the quality of the recommendation service based on precision, satisfactory and applicability. This paper will discuss the proposed WUL-based mining approach, and give the performance of the proposed approach in comparison with the Apriori-based algorithms

An Effective Approach for Periodic Web Personalization

Periodic Web personalization aims to recommend the most relevant resources to a user during a specific time period by analyzing the periodic access patterns of the user from Web usage logs. In this paper, we propose a novel Web usage mining approach for supporting effective periodic Web personalization. The proposed approach first constructs a user behavior model, called personal Web usage lattice, from Web usage logs using the fuzzy formal concept analysis technique. Based on the personal Web usage lattice, resources that the user is most probably interested in during a given period can be deduced efficiently. This approach enables the costly personalized resources preparation process to be done in advance rather than in real-time. The performance evaluation of the proposed periodic Web personalization approach is also given in the paper

A lattice-based approach for chemical structural retrieval

Searching for chemica lstructures with similarstructural and functional information of organic chemicals is an important part of the drug discovery process. However, the current chemical structural retrieval methods have focused mainly on finding chemicals with similar structures to the input chemical structural query, and tend to ignore the functional features which are important for determining the chemical property and activity of the chemicals. In this paper, we propose a lattice-based approach for chemical structural retrieval. The proposed lattice-based approach is based on Formal Concept Analysis. It retrieves chemical structures that have functional groups and interactions between functional groups similar to the chemical structural query. The performance of the proposed lattice-based approach is evaluated and its promising performance results have shown that the proposed approach is effective for chemical structural retrieval

Discovering and Visualizing Temporal-Based Web Access Behavior

Discovering and understanding Web users' surfing behavior are essential for the development of successful Web monitoring and recommendation systems. In this paper, we propose a Web usage mining approach for the automatic discovery and visualization of temporal-based Web access behavior of individual users by mining client-side logs. The proposed approach is based on a Web usage lattice model which represents a hierarchy of Web access activities. To describe such Web access activities, we incorporate fuzzy logic to represent real life temporal concepts such as morning, afternoon and evening, and meaningful Web categories such as news, sports and chat. Based on the lattice, temporal and association behavior patterns can be extracted and visualized

Report on an announced inspection of HM Prison Swaleside on 3-7 February 1997 by HM Chief Inspection of Prisons Report of a full inspection; Part B - main report

SIGLEAvailable from British Library Document Supply Centre-DSC:GPE/1592 / BLDSC - British Library Document Supply CentreGBUnited Kingdo