Algorithms for clustering data

How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

The knowledge-creating company : how Japanese companies create the dynamics of innovation

MKT 6009 Marketing Internship (0 semester credit hours) Student gains experience and improves skills through appropriate developmental work assignments in a real business environment. Student must identify and submit specific business learning objectives at the beginning of the semester. The student must demonstrate exposure to the managerial perspective via involvement or observation. At semester end, student prepares an oral or poster presentation, or a written paper reflecting on the work experience. Student performance is evaluated by the work supervisor. Pass/Fail only. Prerequisites: (MAS 6102 or MBA major) and department consent required. (0-0) S MKT 6244 Digital Marketing Strategy (2 semester credit hours) Executive Education Course. The course explores three distinct areas within marketing and sales namely, digital marketing, traditional sales prospecting, and executive sales organization and strategy. The continuing convergence of the digital marketing and sales funnels has created a strategic continuum from digital lead generation to digital sales. The course identifies the current composition of this digital continuum while providing opportunities to evaluate sales and marketing digital strategies. Prerequisites: MKT 6301 and instructor consent required. (2-0) Y MKT 6301 (SYSM 6318) Marketing Management (3 semester credit hours) Overview of marketing management methods, principles and concepts including product, pricing, promotion and distribution decisions as well as segmentation, targeting and positioning. (3-0) S MKT 6309 Marketing Data Analysis and Research (3 semester credit hours) Methods employed in market research and data analysis to understand consumer behavior, customer journeys, and markets so as to enable better decision-making. Topics include understanding different sources of data, survey design, experiments, and sampling plans. The course will cover the techniques used for market sizing estimation and forecasting. In addition, the course will cover the foundational concepts and techniques used in data visualization and \"story-telling\" for clients and management. Corequisites: MKT 6301 and OPRE 6301. (3-0) Y MKT 6310 Consumer Behavior (3 semester credit hours) An exposition of the theoretical perspectives of consumer behavior along with practical marketing implication. Study of psychological, sociological and behavioral findings and frameworks with reference to consumer decision-making. Topics will include the consumer decision-making model, individual determinants of consumer behavior and environmental influences on consumer behavior and their impact on marketing. Prerequisite: MKT 6301. (3-0) Y MKT 6321 Interactive and Digital Marketing (3 semester credit hours) Introduction to the theory and practice of interactive and digital marketing. Topics covered include: online-market research, consumer behavior, conversion metrics, and segmentation considerations; ecommerce, search and display advertising, audiences, search engine marketing, email, mobile, video, social networks, and the Internet of Things. (3-0) T MKT 6322 Internet Business Models (3 semester credit hours) Topics to be covered are: consumer behavior on the Internet, advertising on the Internet, competitive strategies, market research using the Internet, brand management, managing distribution and supply chains, pricing strategies, electronic payment systems, and developing virtual organizations. Further, students learn auction theory, web content design, and clickstream analysis. Prerequisite: MKT 6301. (3-0) Y MKT 6323 Database Marketing (3 semester credit hours) Techniques to analyze, interpret, and utilize marketing databases of customers to identify a firm's best customers, understanding their needs, and targeting communications and promotions to retain such customers. Topics

Marketing for management.

Emotion and Adaptation

This project aims at establishing basic theories and fundamental methodologies for synthesis through knowledge systematization by exploiting the artificial intelligence technology, especially Ontological Engineering. The concrete objectives of the project include development several kinds of ontologies for knowledge systematization and development of a multi-agent collaborative synthesis framework. The formers mainly concerned with the domain-independent design object knowledge and the latter with domain-independent design process knowledge. This paper report on the intermediate results in the middle of the project term(five years) as well as on the future plan.

A Methodology of Collaborative Synthesis by Artificial Intelligence

In order to formalize complex and compositional concepts, we propose a logical framework based on an upper ontology constructed from the composition of basic concepts such as properties and objects. In particular, ontologically distinct compositions (called ontological compositions) that are not easily defined by using ISA and PART-OF relations are classified into characterizing, temporal, and spatial compositions (e.g., ’red face’ and ’today’). In this paper, we precisely model such ontological compositions by using monadic second-order logic; properties and objects are expressed as predicates, and attributes are expressed as predicates of predicates. The proposed approach provides a novel technique for the classification of attributes as higher-order concepts, and it clarifies illegal compositions of properties and objects and the uniqueness of temporal attributes. Moreover, our composition ontology is described by a set of RDF triples using the metamodeling of concepts in RDF Schema.

http://www.sw.cei.uec.ac.jp/kaneiwa/kk-ngc14.pdf

A Logical and Ontological Framework for Compositional Concepts of Objects and Properties

SWEL’07: Ontologies and Semantic Web Services for Intelligent Distributed Educational Systems : Supplementary Proceedings of the 13th International Conference of Artificial Intelligence in Education (AIED 2007)

As one of the ultimate goals of research in any domain, knowledgestructuring has been carried out to date through the writing of papers and books as part of ordinary academic research activities. In this respect, what scholars are aiming at in the knowledge-structuring of sustainability science (hereafter referred to as SS) might seem to be nothing special. Nevertheless, SS researchers are particularly dedicated to the structuring of knowledge. There are two reasons for this

The structuring of knowledge based on ontology engineering

In the continuously uttered speech, it is often difficult to extract the features of the individual phoneme due to the interaction between phonemes called co-articulation. In such a case, a large amount of empirical knowledge is required for recognition. In the past, efforts have been made to realize the continuous speech recognition system by a procedural language such as FORTRAN, producing problems in the flexibility and expandability of the system. This paper describes the expert system SPREX for continuous speech recognition, which aims at the solution of those problems by introducing knowledge engineering techniques into the speech recognition. The proposed system is an expert system which simulates the behavior of a human expert by the knowledge engineering technique, where the phonemes are recognized by observing the time-course of change of the acoustic feature parameters such as formant frequencies. The system can efficiently manage and utilize the empirical rules inherent to the continuous speech recognition. At present, the system is composed of 114 expert knowledges represented by production rules. The recognition rate of 85 percent is realized for 29-s speech uttered by 3 adult males. Finally, problems left for the studies in this direction are discussed, aiming at the amalgamation of the study of speech and the knowledge engineering.

Riichiro Mizoguchi

Papers

A Methodology of Collaborative Synthesis by Artificial Intelligence

A Logical and Ontological Framework for Compositional Concepts of Objects and Properties

SWEL’07: Ontologies and Semantic Web Services for Intelligent Distributed Educational Systems : Supplementary Proceedings of the 13th International Conference of Artificial Intelligence in Education (AIED 2007)

The structuring of knowledge based on ontology engineering

A continuous speech recognition expert system—sprex