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Frequent Pattern Tree (FP-Tree) is a compact data structure of representing frequent itemsets. The construction of FP-Tree is very important prior to frequent patterns mining. However, there have been too limited efforts specifically focused on constructing FP-Tree data structure beyond from its original database. In typical FP-Tree construction, besides the prior knowledge on support threshold, it also requires two database scans; first to build and sort the frequent patterns and second to build its prefix paths. Thus, twice database scanning is a key and major limitation in completing the construction of FP-Tree. Therefore, this paper suggests scalable Trie Transformation Technique Algorithm (T3A) to convert our predefined tree data structure, Disorder Support Trie Itemset (DOSTrieIT) into FP-Tree. Experiment results through two UCI benchmark datasets show that the proposed T3A generates FP-Tree up to 3 magnitudes faster than that the benchmarked FP-Growth.

The ability for a product developer to successfully launch useful products is tied to the company’s product design strategies. Due to the complexity of perception and expectations on new product design from customers and the diverse perspectives of the product developer, any approaches without systematically analyzing these complex criteria to assess decision making on product design strategies are therefore deemed as inappropriate. A systematic approach to determine appropriate product design strategies based on the attributes of product design and customer expectations should thus be considered. This research focuses on the investigation of shape formulation process using evolutionary grammars (EG) and non-linear product design analysis with Kano model to refine product design strategies. Through the strategic integration of evolutionary grammars and Kano model, the complex effects on the evolutionary design process and product design strategies are revealed. In order to demonstrate the viability of the approach, experiments are described and a comparison analysis on three EG-Kano reference models is performed. Upon determining the appropriate EG-Kano reference model, the product developer can refine the product design strategies to suit the targeted market.

Cloud computing is fundamentally altering the expectations for how and when computing, storage, and networking resources should be allocated, managed, consumed, and allow users to utilize services globally. Due to the powerful computing and storage, high availability and security, easy accessibility and adaptability, reliable scalability and interoperability, cost and time effective cloud computing is the top, needed for current fast growing business world. A client, organization or a trade that adopting emerging cloud environment can choose a well suitable infrastructure, platform, software, and a network resource, for any business, where each one has some exclusive features and advantages. The authors first develop a comprehensive classification for describing cloud computing architecture. This classification help in survey of several existing cloud computing services developed by various projects globally such as Amazon, Google, Microsoft, Sun and Force.com and by using this survey’s results the authors identified similarities and differences of the architecture approaches of cloud computing.

Internet has brought a major drift in user community. Apart from its well-known usage, it also promotes social networking. Research on such social networking has advanced significantly in recent years which have been highly influenced by the online social websites. People perceive the web as a social medium that allows larger interaction among people, sharing of knowledge, or experiences. Internet or social web forums act as an agent to reproduce some general information that would benefit the users. A product review by the user is a more accurate representation of its real-world performance and web-forums are generally used to post such reviews. Though commercial review websites allow users to express their opinions in whatever way they feel, the number of reviews that a product receives could be very high. Hence, opinion mining techniques can be used to analyze the user-reviews, classify the content as positive or negative, and thereby find out how the product fares. This paper focuses its attention on providing a recommendation to the products available on the web by analyzing the context to score the sentences for each review by identifying the opinion and feature words using a novel algorithm.

In the 21st century, the awareness of applying recent advanced intelligent technologies to promote a firm's brand image is the key to the success of expanding its business. Such implication demands efforts in strategic planning and massive investment from the top management team. However, most researches on branding strategies are narrowed to advertisement or classical marketing. Insufficient research on the backbone of making key successful branding strategies to effectively apply the intelligent technologies hinders the development of branding strategies. This chapter identifies three aspects: innovation in design technology, decision making on product quality, and collaborative communications to be the critical elements of the backbone. The methodology utilizes the power of the advanced computational technologies to generate innovative designs in a collaborative communication framework. Decision making on the quality of designs is monitored with EG-Kano reference models. Four case studies demonstrate that the backbone has potentials leading to ever-greater economic benefits.