Knowledge Discovery from Web Logs - A Survey

Web usage mining is obtaining the interesting and constructive knowledge and implicit information from activities related to the WWW. Web servers trace and gather information about user interactions every time the user requests for particular resources. Evaluating the Web access logs would assist in predicting the user behavior and also assists in formulating the web structure. Based on the applications point of view, information extracted from the Web usage patterns possibly directly applied to competently manage activities related to e-business, e-services, e-education, on-line communities and so on. On the other hand, since the size and density of the data grows rapidly, the information provided by existing Web log file analysis tools may possibly provide insufficient information and hence more intelligent mining techniques are needed. There are several approaches previously available for web usage mining. The approaches available in the literature have their own merits and demerits. This paper focuses on the study and analysis of various existing web usage mining techniques

Adoption of ubiquitous crm for operational sustainability of the firms: Moderating role of technology turbulence

Ubiquitous CRM (UCRM) enhances customer relationship management. It can sense customer needs and demands, to which firms can respond quickly. Therefore, UCRM helps to improve a firm’s agility. There is a growing interest among researchers and practitioners to understand how the adoption of UCRM impacts the sustainability of firms’ operations, but not many studies have investigated this issue. In this context, the aim of this study is to examine how firms’ absorptive capacity and dynamic capability could impact the adoption of UCRM to influence the operational sustainability of the firms and their performance. The study also investigates the moderating role of technology turbulence on the relationship between a firm’s operational sustainability and its per-formance. Using absorptive capacity theory and dynamic capability view theory and reviewing the existing literature, we developed a conceptual model. The model was then validated using a structural equation modeling technique considering 309 usable respondents from different firms that use UCRM for their operational activities. The study found that firms’ absorptive capacity and dynamic capability significantly and positively impact the adoption of UCRM, which in turn significantly and positively impacts firms’ operational sustainability and improves their performance. The study also shows that there is a significant moderating role of technology turbulence on the relationship between operational sustainability and firm performance

Fuzzy qualitative trigonometry

AbstractThis paper presents a fuzzy qualitative representation of conventional trigonometry with the goal of bridging the gap between symbolic cognitive functions and numerical sensing & control tasks in the domain of physical systems, especially in intelligent robotics. Fuzzy qualitative coordinates are defined by replacing a unit circle with a fuzzy qualitative circle; a Cartesian translation and orientation are defined by their normalized fuzzy partitions. Conventional trigonometric functions, rules and the extensions to triangles in Euclidean space are converted into their counterparts in fuzzy qualitative coordinates using fuzzy logic and qualitative reasoning techniques. This approach provides a promising representation transformation interface to analyze general trigonometry-related physical systems from an artificial intelligence perspective.Fuzzy qualitative trigonometry has been implemented as a MATLAB toolbox named XTRIG in terms of 4-tuple fuzzy numbers. Examples are given throughout the paper to demonstrate the characteristics of fuzzy qualitative trigonometry. One of the examples focuses on robot kinematics and also explains how contributions could be made by fuzzy qualitative trigonometry to the intelligent connection of low-level sensing & control tasks to high-level cognitive tasks

Direct Marketing Based on Fuzzy Clustering of Customers (Case Study: on one Mobile Company)

Objective There is a general tendency toward direct marketing these days. Therefore, instead of designing advertisement and marketing strategies for all the customers in the market, it is recommended to classify the customers based on clustering techniques and then design specific strategies accordingly. This will reduce marketing and advertisement expenses, increase sale department efficiently, build closer and quicker relationships with different customers and etc. There are a variety of clustering methods. Provided that clustering means classifying customers in different groups with maximum similarities within the groups and maximum difference among the groups, it may not be appropriate to apply such a rule in clustering customers (people) due to their nature. Hence, fuzzy clustering technique seems more appropriate for customers because there are no absolute borders considered among different groups just as the market suggests. This study, then, aims to emphasize on this concept in order to apply fuzzy clustering on market.   Methodology This practical research is descriptive-exploratory in nature of data collection. The statistical population includes all the customers of a mobile company, but due to availability issues only a part of their customers would be involved in the present study. A questionnaire including 6 questions was distributed among those customers and only 760 were correctly responded. Finally, EXCEL and S-PLUS were used to analyze the data.    Findings The data in this study include three different parts of information. The first part includes some indexes selected for analysis of the clustering. Second part concerns with the customers service usage such as distant phone calls, free calls and wireless services. The third part refers to other mobile services provided for each customer. This part is presented in a binary fashion deciding whether a customer has received a specific service or not. Such services include activating more than one mobile line at the moment, using voicemail, paging, internet and other services. This algorithm was used to conduct fuzzy clustering in the present study. Following applying fuzzy clustering, only 2 clusters were judged appropriate for such data. The first cluster includes customers with lower income, job stability and lower loyalty to the mobile company, while the second cluster includes customers with higher income, higher job stability and more loyalty to the mobile company. The customers in the first cluster used services like free calls, wireless networks and pay phones. On the other hand, the customer in the second cluster mainly used services like distant calls and rarely used wireless services. In general, we can claim that paging services were the highest requested and then there are voicemail services, internet, and e-pay services respectively. The two clusters reported to have a similar tendency in using services such as voicemail, multi-lines, conferencing; yet, they were different in services like paging, internet, call forwarding (diverting), call waiting and e-pay services. At the end, mobile companies can set marketing strategies based on such findings.   Conclusion It is suggested that mobile companies focus on general advertisements and distant call services, but only a little focus on wireless services. They can also put more thought on services like paging, voicemail, internet and e-pay services respectively. It is also recommended that, for female customers (mostly within the first cluster), the companies should focus on pay phone services, distant calls, and free calls as well as voicemail and internet. On the other hand, for male customer with higher job stability, it is suggested to focus the most on distant call services and provision of special discounts with this regard, but the least on wireless and pay phone services. Besides, voicemail services, paging, call waiting, call forwarding and e-pay services should be the mobile company’s priority for male customers

Personalized advertisement assignment system

This thesis presents a comprehensive framework which will be used to maximize the advertising revenues of a company that develops a 3-D virtual reality social platform. The comprehensive framework includes the development of a personalized advertising business model for the company, representation of the business model with a mathematical program and proposing a set of heuristic solutions for the personalized advertising problem. The proposed heuristics are developed and their performances are compared with an experimental analysis under various conditions

Aplicação de marketing analítico na farmácia Gaia Jardim

O projecto apresentado surgiu no âmbito de uma proposta de investigação da Católica Porto Business School. Cada vez mais, os sistemas de informação fazem parte do desenvolvimento das empresas e a Farmácia Gaia Jardim procurou evoluir nesse sentido e utilizar a sua base de dados para desenvolver a sua relação com os clientes. Assim, neste trabalho pretendeu-se estabelecer estratégias de cross-selling através do uso de ferramentas de marketing analítico, nomeadamente data mining. De um modo geral, esta análise aos dados da farmácia permitiu um maior conhecimento sobre os seus clientes. Mais concretamente, este trabalho permitiu a identificação dos segmentos de clientes com base na frequência de visitas à fármacia e o valor médio gasto e a criação de regras de associação entre produtos para estabelecer as estratégias de cross-selling mais adequadas para cada segemento de clientes da farmácia.The presented project is developed in the scope of a research proposal from Católica Porto Business School. Information systems are becoming of increased importance to the development of companies. Gaia Jardim Pharmacy is taking this fact into consideration and using its data base to develop their relationship with their customers. Therefore, in this paper we aimed at creating cross-selling strategies through of the use of analytic marketing tools, as data mining. In general, this analysis enabled to obtain a more detailed knowledge about the customers of the pharmacy. uMore specifically, this study enabled the identification of segments of customers and finally on the identification of association rules between the products which allows the pharmacy to definethe most adequate cross-selling strategies for the segments of customers identified