Kôiti Hasida

POLYPHONET: an advanced social network extraction system from the web

Social networks play important roles in the Semantic Web: knowledge management, information retrieval, ubiquitous computing, and so on. We propose a social network extraction system called POLYPHONET, which employs several advanced techniques to extract relations of persons, detect groups of persons, and obtain keywords for a person. Search engines, especially Google, are used to measure co-occurrence of information and obtain Web documents.Several studies have used search engines to extract social networks from the Web, but our research advances the following points: First, we reduce the related methods into simple pseudocodes using Google so that we can build up integrated systems. Second, we develop several new algorithms for social networking mining such as those to classify relations into categories, to make extraction scalable, and to obtain and utilize person-to-word relations. Third, every module is implemented in POLYPHONET, which has been used at four academic conferences, each with more than 500 participants. We overview that system. Finally, a novel architecture called Super Social Network Mining is proposed; it utilizes simple modules using Google and is characterized by scalability and Relate-Identify processes: Identification of each entity and extraction of relations are repeated to obtain a more precise social network.

POLYPHONET: An advanced social network extraction system from the Web

Social networks play important roles in the Semantic Web: knowledge management, information retrieval, ubiquitous computing, and so on. We propose a social network extraction system called POLYPHONET, which employs several advanced techniques to extract relations of persons, to detect groups of persons, and to obtain keywords for a person. Search engines, especially Google, are used to measure co-occurrence of information and obtain Web documents. Several studies have used search engines to extract social networks from the Web, but our research advances the following points: first, we reduce the related methods into simple pseudocodes using Google so that we can build up integrated systems. Second, we develop several new algorithms for social network mining such as those to classify relations into categories, to make extraction scalable, and to obtain and utilize person-to-word relations. Third, every module is implemented in POLYPHONET, which has been used at four academic conferences, each with more than 500 participants. We overview that system. Finally, a novel architecture called Iterative Social Network Mining is proposed. It utilizes simple modules using Google and is characterized by scalability and relate-identify processes: identification of each entity and extraction of relations are repeated to obtain a more precise social network.

Semantics of multimedia in MPEG-7

In this paper, we present the tools standardized by MPEG-7 for describing the semantics of multimedia. In particular, we focus on the abstraction model, entities, attributes and relations of MPEG-7 semantic descriptions. MPEG-7 tools can describe the semantics of specific instances of multimedia such as one image or one video segment but can also generalize these descriptions either to multiple instances of multimedia or to a set of semantic descriptions. The key components of MPEG-7 semantic descriptions are semantic entities such as objects and events, attributes of these entities such as labels and properties, and, finally, relations of these entities such as an object being the patient of an event. The descriptive power and usability of these tools has been demonstrated in numerous experiments and applications, these make them key candidates to enable intelligent applications that deal with multimedia at human levels.

MIKE: an automatic commentary system for soccer

This paper describes MIKE, an automatic commentary system for the game of soccer. Since soccer is played by teams, describing the course of a game calls for reasoning about multi-agent interactions. Also, events may occur at any point of the field at any time, making it difficult to fix viewpoints. MIKE interprets this domain with six soccer analysis modules that run concurrently within a role-sharing framework. We describe these analysis modules and also discuss how to control the interaction between them so that an explanation of a game emerges reactively from the system. We present and evaluate examples of the match commentaries produced by MIKE in English, Japanese and French.

Semantic authoring and semantic computing

Semantic Computing is to design and operate information systems based on meaning and vocabulary shared by people and computers. It aims at closing the semantic gap, thus enabling closer cooperation between people and information systems, and thereby semantically enriching our life-world. Ontologies and constraints are major technologies to let people and information systems share common meaning. Semantic authoring is to compose information content together with explicit semantic structure based on ontologies. This not only reduces the cost of content composition but also improves the quality of the resulting content, by both freeing the author from worries about the order of presentation and providing her a perspicuous view of the logical content structure. Social interactions are much more generally modelled in terms of constraints than in terms of workflows or procedures. CBTO (compositional business-task organization) is a constraint-based framework to concisely describe uniformities of social interactions and thus provides a semantic-level scheme for coordinating various, possibly interactive, services with each other.

Rotation invariant feature extraction from 3-D acceleration signals

In this paper, we propose a method to extract features from three-dimensional acceleration signals. The proposed method is based on the (auto-)correlation matrix of Fourier transform features, naturally containing the correlations between the frequencies as well as the ordinary power spectrum for each frequency. The proposed features are inherently invariant to both rotational variations and temporal shift (delay), whereas the other methods employ ad hoc preprocessing to increase robustness to those variations. Thereby, we can favorably apply the proposed method to analyze 3-D acceleration signals regardless of the orientations of the accelerometer. In the experiment on gait identification using an accelerometer embedded in a cellular phone, the proposed method outperformed the other methods.

Automatic Soccer Commentary and RoboCup

This paper suggests that automated soccer commentary has a key role to play within the overall RoboCup initiative. Firstly, we identify soccer commentary as allowing and requiring investigation of a wide variety of research topics, many of which could not be addressed by the simple development of teams for the RoboCup leagues themselves. Secondly, we highlight a key task of soccer commentary: the expert analysis of a game. We suggest that this expert analysis task has the potential to make a significant impact on RoboCup challenges such as learning, teamwork, and opponent modeling. We illustrate our arguments by discussing the progress on soccer commentary systems to date, in particular reviewing our own system, MIKE.

Knowledge worker intranet behaviour and usability

Understanding human behaviour in electronic spaces is of central importance in modern business intelligence and web behaviour mining. We present a novel analytic framework that enables identification of the significant navigational elements, observation of higher order behavioural abstractions, and investigation of usability attributes. A case study of knowledge worker intranet browsing behaviour revealed elemental and complex browsing pattern formation. Frequent patterns were relatively easily executable. Knowledge workers accomplished browsing goals via few subtasks, had focused targets, and accessed narrow range of services and resources. A diminutive exploratory behaviour and significant underutilisation of available resources were exhibited.

Reactive Content Selection in the Generation of Real-time Soccer Commentary

MIKE is an automatic commentary system that generates a commentary of a simulated soccer game in English, French, or Japanese.One of the major technical challenges involved in live sports commentary is the reactive selection of content to describe complex, rapidly unfolding situation. To address this challenge, MIKE employs importance scores that intuitively capture the amount of information communicated to the audience. We describe how a principle of maximizing the total gain of importance scores during a game can be used to incorporate content selection into the surface generation module, thus accounting for issues such as interruption and abbreviation.Sample commentaries produced by MIKE are presented and used to evaluate different methods for content selection and generation in terms of efficiency of communication.

Conditioned unification for natural language processing

This paper presents what we call a conditional unification a new method of unification for processing natural languages. The key idea is to annotate the patterns with a certain sort of conditions, so that they carry abundant information. This method transmits information from one pattern to another more efficiently than procedure attachments, in which information contained in the procedure is embedded in the program rather than directly attached to patterns. Coupled with techniques in formal linguistics, moreover, conditioned unification serves most types of operations for natural language processing.