The article reviews the book “Information Rules: A Strategic Guide to the Network Economy,” by Carl Shapiro and Hal R. Varian.

Information Rules: A Strategic Guide to the Network Economy

Suggested by the structure of the visual nervous system, a new algorithm is proposed for pattern recognition. This algorithm can be realized with a multilayered network consisting of neuron-like cells. The network, “neocognitron”, is self-organized by unsupervised learning, and acquires the ability to recognize stimulus patterns according to the differences in their shapes: Any patterns which we human beings judge to be alike are also judged to be of the same category by the neocognitron. The neocognitron recognizes stimulus patterns correctly without being affected by shifts in position or even by considerable distortions in shape of the stimulus patterns.

Neocognitron--A New Algorithm for Pattern Recognition Tolerant of Deformations and Shifts in Position

In the last 16 years, more than 200 research articles were published about research-paper recommender systems. We reviewed these articles and present some descriptive statistics in this paper, as well as a discussion about the major advancements and shortcomings and an overview of the most common recommendation concepts and approaches. We found that more than half of the recommendation approaches applied content-based filtering (55 %). Collaborative filtering was applied by only 18 % of the reviewed approaches, and graph-based recommendations by 16 %. Other recommendation concepts included stereotyping, item-centric recommendations, and hybrid recommendations. The content-based filtering approaches mainly utilized papers that the users had authored, tagged, browsed, or downloaded. TF-IDF was the most frequently applied weighting scheme. In addition to simple terms, n-grams, topics, and citations were utilized to model users' information needs. Our review revealed some shortcomings of the current research. First, it remains unclear which recommendation concepts and approaches are the most promising. For instance, researchers reported different results on the performance of content-based and collaborative filtering. Sometimes content-based filtering performed better than collaborative filtering and sometimes it performed worse. We identified three potential reasons for the ambiguity of the results. (A) Several evaluations had limitations. They were based on strongly pruned datasets, few participants in user studies, or did not use appropriate baselines. (B) Some authors provided little information about their algorithms, which makes it difficult to re-implement the approaches. Consequently, researchers use different implementations of the same recommendations approaches, which might lead to variations in the results. (C) We speculated that minor variations in datasets, algorithms, or user populations inevitably lead to strong variations in the performance of the approaches. Hence, finding the most promising approaches is a challenge. As a second limitation, we noted that many authors neglected to take into account factors other than accuracy, for example overall user satisfaction. In addition, most approaches (81 %) neglected the user-modeling process and did not infer information automatically but let users provide keywords, text snippets, or a single paper as input. Information on runtime was provided for 10 % of the approaches. Finally, few research papers had an impact on research-paper recommender systems in practice. We also identified a lack of authority and long-term research interest in the field: 73 % of the authors published no more than one paper on research-paper recommender systems, and there was little cooperation among different co-author groups. We concluded that several actions could improve the research landscape: developing a common evaluation framework, agreement on the information to include in research papers, a stronger focus on non-accuracy aspects and user modeling, a platform for researchers to exchange information, and an open-source framework that bundles the available recommendation approaches.

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Research-paper recommender systems: a literature survey

This paper surveys and analyzes the state of the art of agent-mediated electronic commerce (e-commerce), concentrating particularly on the business-to-consumer (B2C) and business-to-business (B2B) aspects. From the consumer buying behavior perspective, agents are being used in the following activities: need identification, product brokering, buyer coalition formation, merchant brokering, and negotiation. The roles of agents in B2B e-commerce are discussed through the business-to-business transaction model that identifies agents as being employed in partnership formation, brokering, and negotiation. Having identified the roles for agents in B2C and B2B e-commerce, some of the key underpinning technologies of this vision are highlighted. Finally, we conclude by discussing the future directions and potential impediments to the wide-scale adoption of agent-mediated e-commerce.

Agent-Mediated Electronic Commerce

Manufacturing process planning is the process of selecting and sequencing manufacturing processes such that they achieve one or more goals and satisfy a set of domain constraints. Manufacturing scheduling is the process of selecting a process plan and assigning manufacturing resources for specific time periods to the set of manufacturing processes in the plan. It is, in fact, an optimization process by which limited manufacturing resources are allocated over time among parallel and sequential activities. Manufacturing process planning and scheduling are usually considered to be two separate and distinct phases. Traditional optimization approaches to these problems do not consider the constraints of both domains simultaneously and result in suboptimal solutions. Without considering real-time machine workloads and shop floor dynamics, process plans may become suboptimal or even invalid at the time of execution. Therefore, there is a need for the integration of manufacturing process-planning and scheduling systems for generating more realistic and effective plans. After describing the complexity of the manufacturing process-planning and scheduling problems, this paper reviews the research literature on manufacturing process planning, scheduling as well as their integration, particularly on agent-based approaches to these difficult problems. Major issues in these research areas are discussed, and research opportunities and challenges are identified

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Agent-based distributed manufacturing process planning and scheduling: a state-of-the-art survey

This paper is to examine interactive integrative learning support system for elementary school students. Our Web-based system enables a group of some 5 students and teachers to learn interactively by collaboratively creating outcome (i.e. Web pages) through a shared Web site. Three main functions of the system are followings;(1)To build a shared Web site directly from Web browser in order to support students and teachers who are inexperienced in composing HTML. (2) To modify and edit a shared Web site directly from portable terminals to support students at on-site training in real time. (3) An agent function that supports plan modifications and rerouting in case of students choose a wrong route. We have applied our system to research training and on-site training of elementary school students who are studying in a group as a part of integrative learning curriculum.

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An Interactive Learning System in Elementary Schools

In this paper, we propose a web browsing support system, called WPM, which provides marking and anchoring functions on ordinary web browsers. WPM users can mark words and phrases on web pages by using their browsers without any extra plug-ins like similar systems, and can anchor words to refer them later. WPM makes it possible to carry out marking to the existing Web page so that marking carried out to paper. By changing character decoration partially, the text is indicated by emphasis and improve readability. WPM is implemented using proxy agent. This system can be used in everyday browsing, without a user being conscious of a system by using a proxy.

https://www.ra.ethz.ch/CDStore/www2005/docs/p1012.pdf

Web page marker: a web browsing support system based on marking and anchoring

Volume discount is seen as an effective form of electronic commerce and a promising field for applying agent technologies. In current volume discount mechanisms, items are not allocated efficiently to buyers. Namely, social surplus is not maximum in existing volume discount schemes. To solve this problem, we propose a volume discount mechanism based on the seller's reservation price and the payment adjustment value. First, a seller registers his/her items with the evaluation value functions. The seller's evaluation value is sealed and each buyer bids his/her evaluation value as sealed bid. After the deadline, the mechanism determines the allocation of bundles of items. A tentative price is decided and the payment adjustment value is calculated. Finally, the payment amount is calculated. Our mechanism has some key advantages. First, the mechanism is Pareto efficient. Second, our mechanism is a strategy-proof mechanism, that is, it has the incentive compatibility. Third, our mechanism provides individual rationality. Fourth, our mechanism is made based on the volume discount system, where the seller can give a signal indicating a discount for buyers. Finally, our mechanism weakens the influence of false name bids.

An approach to avoiding shill bids based on combinatorial auction in volume discount

We propose a method of classifying XML documents and extracting XML schema from XML by inductive inference based on constraint logic programming. The goal of this work is to type a large collection of XML approximately but efficiently. This can also process XML code written in a different schema or even code which is schema-less. Our approach is intended to achieve identification based on the syntax and semantics of the XML documents by information extraction using ontology, and to support retrieval and data management. Our approach has three steps. The first step is XML to predicates, the second step is to compare predicates and classifies structures which represent similar meanings in different structures, and the last step is predicates to rules by using ontology and to maintain XML Schema. We evaluate similarity of data type and data range by using an ontology dictionary, and XML Schema is made from results of second and last step.

Extracting XML schema from multiple implicit xml documents based on inductive reasoning

We implemented a synchronization module for tablet devices to support collaborative works based on Web contents. The module enables multiple tablet devices to display web contents as one large display. In this paper, we show the implementation of the module. Pair swipe operations are adopted to determine the position of the device and the UDP is used for broadcasting synchronous messages. We show two applications based on the synchronization module, one is a piano score system, and map viewing system.

Toramatsu Shintani

Papers

An Interactive Learning System in Elementary Schools

Web page marker: a web browsing support system based on marking and anchoring

An approach to avoiding shill bids based on combinatorial auction in volume discount

Extracting XML schema from multiple implicit xml documents based on inductive reasoning

On a Synchronizing Module for Extended Web Displaying System Based on Multiple Tablet Devices