This paper overviews NTCIR-13 Actionable Knowledge Graph (AKG) task. The task focuses on finding possible actions related to input entities and the relevant properties of such actions. AKG is composed of two subtasks: Action Mining (AM) and Actionable Knowledge Graph Generation (AKGG). Both subtasks are focused on English language. 9 runs have been submitted by 4 teams for the task. In this pap...

This paper describes an application of data mining to detecting misconducts, such as use of bots and cheats, in Massively Multiplayer Online Role-Playing Games (MMORPGs). A method is proposed that exploits the information on action frequencies, types, and intervals available in the targeted MMORPG log data. The aforementioned information is used as the input to a support vector machine. Evaluat...

Implicit user modeling has always long since played an important role in supporting personalized web-based e-learning environments and is increasingly important in other learning environments such as serious games. Its main concern is to unobtrusively and ubiquitously learn from a learner’s previous experiences and characteristics, in order to adapt the services to their personal needs. An empi...

the purpose of this study was to examine how four teachers used the seven processes of videotape analysis to develop an analytic approach and reflective thinking towards their teaching. the study was organized within video clubs and was used to describe the interactions among four teachers about their experiences at a language institute. data were gathered through videotaped recordings of lesso...

AbstrAct Multi-agent system is specialized in studying the collective effects of multiple intelligent agents. An intelligent agent is a computer system with autonomous action in an environment. This technology is especially suitable for studying geospatial phenomena since they are complex in nature and call for intertwined actions from different forces. This chapter describes multi-agent system...

This paper advances the state of the art in text understanding of medical guidelines by releasing two new annotated clinical guidelines datasets, and establishing baselines for using machine learning to extract condition-action pairs. In contrast to prior work that relies on manually created rules, we report experiment with several supervised machine learning techniques to classify sentences as...

In silico target fishing is an emerging technology that enables the prediction of biological targets of compounds on the basis of chemical structure by using information from increasingly available biologically annotated chemical databases. We provide a comparative review of recent studies in which data mining, similarity, or docking of chemical structures is used to elucidate target class or m...

In this paper we define the notion of causal chains. Causal chains are a particular kind of sequential patterns that reflect causality relations according to background knowledge. We also present an algorithm for mining causal chains from a collection of action traces. We run this algorithm on a realworld domain and observe that causal chains can be computed efficiently by quickly identifying i...

soil erosion causes sediments to be detached from their source materials and transported as suspended particles. the present study was conducted to evaluate the effects of sand exploitation on the distribution of suspended sediments in the educational and research forest watershed of tarbiat modares university, which comprises approximately 50,000 ha. fifty-one water samples were collected befo...