A dynamic knowledge base based search engine

Search engines have greatly helped us to find the desired information from the Internet. Most search engines use keywords matching technique. This paper discusses a Dynamic Knowledge Base based Search Engine （DKBSE）, which can expand the user＇s query using the keywords＇ concept or meaning. To do this, the DKBSE needs to construct and maintain the knowledge base dynamically via the system＇s searching results and the user＇s feedback information. The DKBSE expands the user＇s initial query using the knowledge base, and returns the searched information after the expanded query.

ESKD-A New Structure of Expert System Based on Knowledge Discovery

A new structure of ESKD (expert system based on knowledge discovery system KD (D&K)) is first presented on the basis of KD (D&K)-a synthesized knowledge discovery system based on double-base (database and knowledge base) cooperating mechanism. With all new features, ESKD may form a new research direction and provide a great probability for solving the wealth of knowledge in the knowledge base. The general structural frame of ESKD and some sub-systems among ESKD have been described, and the dynamic knowledge base based on double-base cooperating mechanism has been emphased on. According to the result of demonstrative experi- ment, the structure of ESKD is effective and feasible.

Decision Model of Knowledge Transfer in Big Data Environment

A decision model of knowledge transfer is presented on the basis of the characteristics of knowledge transfer in a big data environment.This model can determine the weight of knowledge transferred from another enterprise or from a big data provider.Numerous simulation experiments are implemented to test the efficiency of the optimization model.Simulation experiment results show that when increasing the weight of knowledge from big data knowledge provider,the total discount expectation of profits will increase,and the transfer cost will be reduced.The calculated results are in accordance with the actual economic situation.The optimization model can provide useful decision support for enterprises in a big data environment.

Reasoning about Epistemic Actions and Knowledge in Multi-Agent Systems Using Coq

In this paper, the authors outline a formal system for reasoning about agents＇ knowledge in knowledge games-a special type of multi-agent system. Knowledge games are card games where the agents＇ actions involve an exchange of information with other agents in the game. The authors＇ system is modeled using Coq-a formal proof management system. To the best of the authors＂ knowledge, there are no papers in which knowledge games are considered using a Coq proof assistant. The authors use the dynamic logic of common knowledge, where they particularly focus on the epistemic consequences of epistemic actions carried out by agents. The authors observe the changes in the system that result from such actions. Those changes that can occur in such a system that are of interest to the authors take the form of agents＇ knowledge about the state of the system, knowledge about other agents＇ knowledge, higher-order agents＇ knowledge and so on, up to common knowledge. Besides an axiomatic ofepistemic logic, the authors use a known axiomatization of card games that is extended with some new axioms that are required for the authors＇ approach. Due to a deficit in implementations grounded in theory that enable players to compute their knowledge in any state of the game, the authors show how the authors＇ approach can be used for these purposes.

Big Data Capability,Knowledge Dynamic Capability,and Business Model Innovation:The Moderating Effect of Innovation Legitimacy

Based on dynamic capability theory and legitimacy theory,a theoretical model is constructed to examine how big data capability,through the mediation of knowledge dynamic capability,drive business model innovation under the moderation effect of innovation legitimacy.The eanalys is isconducted using regression analysis and fuzzy set qualitative comparative analysis(fsQCA)on survey data from 302 enterprises that have already implemented big data application practices.The study finds the following four conclusions.(1)Big data capability has a significant positive impact on business model innovation.(2)Dynamic knowledge capability partially mediates the relationship between big data capability and business model innovation.(3)Innovation legitimacy positively influences business model innovation and positively moderates the relationship between big data capability and businessmodel innovation.(4)Through further qualitative comparative analysis,two causal paths that influence business model innovation are identified.