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

Although sentiment polarity is important for under-standing public reputations, conventional web search snippets do not include sentiment polarity. Therefore, we propose a system to generate search result snippets that considers sentiment polarity. We also propose a method for extracting reputation sentences from search result snippets based on a given search query. To extract such sentences, we use a Paragraph Vector (PV) to calculate the similarity of words and sentences. Overall, our method is based on this PV and logistic regression for analyzing sentiment polarities. We evaluated the accuracy of our method via the Rakuten dataset. In our evaluation, we focused on methods pertaining to what supports sentiment polarity analysis in our method. We found that considering both a search query and reputation is important in generating our modified snippets. Furthermore, we identified the need for a method to remove meaningless sentences, which will be part of our future studies.

Sentiment Polarity Analysis for Generating Search Result Snippets Based on Paragraph Vector

Digital picture books increase the interest of children in reading and are often used to encourage children to read. In this study, we develop a digital picture book using the augmented reality (AR) technology, which can be referred to as an AR pop-up picture book (AR book). The AR technology is used to prepare and present digital picture books in the AR space. However, developing an AR book requires technical skills and expertise, which are not possessed by common picture book writers. Therefore, we propose a new intuitive method for obtaining editing effects by teaching motions based on the demonstrations of writers using real-world objects. The results of this study denote that the proposed method is useful for achieving editing effects in AR books, enables writers to achieve editing effects in an AR book, and improves the edit accuracy.

Realizing an Effect Editor for AR Pop-up Picture Books by Teaching Motions

We propose a Drawing-Frequency based Layered (DFL) Canvas approach to reduce a synchronization delay in collaborative web applications. The synchronization delay consists of a network delay and a drawing delay. The network delay is well-argued topic by various researches. We focus on the drawing delay, which is a primary bottleneck of Canvas objects synchronizations. We introduce the DFL Canvas approach in order to solve the drawing problem. The DFL Canvas divides Canvas objects by drawingfrequency. We implemented a collaborative paper editing support system with the DFL Canvas. Users can edit the same document and share Canvas objects on papers in real-time on web browsers. We present an evaluation result that indicates the approach is suited for collaborative paper editing support systems.

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On a Drawing-Frequency based Layered Canvas Mechanism for Collaborative Paper Editing Support Systems

PROBLEM TO BE SOLVED: To provide an information distribution system by which advertisement and information to be displayed on an Web page on WWW can be controlled without delay according to the schedule of an intermediary server. SOLUTION: The intermediary server 10 edits an information display program table T for displaying information of advertisement etc. and sends the latest program table T to a content server 20. When the content server 20 stores an agent script A and the latest program table T and browsing of a content is requested to the content server 20 from a browsing computer 40, the program T and the agent A are sent to the computer 40 with an objective content, and advertisement where the agent script A in the computer 40 is designated by the program table T can be displayed with the content. Thus, without giving excessive communication load to a traffic, change of the program table by the intermediary server 10 is reflected immediately. COPYRIGHT: (C)2006,JPO&NCIPI

Pseudo push type information distribution system on world wide web

Forming effective coalitions is a major problem in multiagent systems. Coalition structure generation (CSG) involves partitioning a set of agents into teams, i.e. coalitions. The set of coalitions is a coalition structure. In the context of the CSG research, our goal is forming the coalition structure that maximizes the social surplus. The social surplus is the sum of utilities obtained by forming coalitions. Calculating the optimal coalition structure is time consuming, therefore recalculating the optimal coalition structure should be avoided when an agent leaves a coalition structure because of sudden reasons such as an accident or an illness. Robust coalition structure generation (RCSG) is CSG focused on the robustness of coalition structures. The robustness of coalition structures is the property that the social surplus is kept at the maximum when any agents leave the coalition structure. We focused on the robustness of each coalition to solve an RCSG problem. Our method finds the optimal coalition structure by considering the robustness of each coalition in the optimal coalition structure. We proposed a coalition lattice, which is a novel data structure to represent the robustness of coalitions. The paper presents an algorithm to construct the coalition lattice from a CSG problem and the result of our evaluation.

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Toramatsu Shintani

Papers

Sentiment Polarity Analysis for Generating Search Result Snippets Based on Paragraph Vector

Realizing an Effect Editor for AR Pop-up Picture Books by Teaching Motions

On a Drawing-Frequency based Layered Canvas Mechanism for Collaborative Paper Editing Support Systems

Pseudo push type information distribution system on world wide web

Coalition Lattice: A Data Structure considering Robustness for Robust Coalition Structure Generation Problem