Search results

This paper aims to propose a system for generating actionable knowledge from Big Data and use this system to construct a comprehensive knowledge base (KB), called GrandBase.

In particular, this study extracts new predicates from four types of data sources, namely, Web texts, Document Object Model (DOM) trees, existing KBs and query stream to augment the ontology of the existing KB (i.e. Freebase). In addition, a graph-based approach to conduct better truth discovery for multi-valued predicates is also proposed.

Empirical studies demonstrate the effectiveness of the approaches presented in this study and the potential of GrandBase. The future research directions regarding GrandBase construction and extension has also been discussed.

To revolutionize our modern society by using the wisdom of Big Data, considerable KBs have been constructed to feed the massive knowledge-driven applications with Resource Description Framework triples. The important challenges for KB construction include extracting information from large-scale, possibly conflicting and different-structured data sources (i.e. the knowledge extraction problem) and reconciling the conflicts that reside in the sources (i.e. the truth discovery problem). Tremendous research efforts have been contributed on both problems. However, the existing KBs are far from being comprehensive and accurate: first, existing knowledge extraction systems retrieve data from limited types of Web sources; second, existing truth discovery approaches commonly assume each predicate has only one true value. In this paper, the focus is on the problem of generating actionable knowledge from Big Data. A system is proposed, which consists of two phases, namely, knowledge extraction and truth discovery, to construct a broader KB, called GrandBase.

This article presents a pedagogical model that utilizes students as primary researchers in the identification, interviewing, and then reporting on women entrepreneurs as a major component of a multidisciplinary entrepreneurship course. The purpose of the course is to attract students who may not be familiar with the entrepreneurship concept itself, the role of women in such economic ventures, or the possibilities for people like themselves in such a career avenue. Students are exposed to the accomplishments of women entrepreneurs throughout U.S. history in the broad categories of agriculture and mining; construction; communication; manufacturing; service (both for profit and not-for-profit); transportation; and wholesale and retail trade. This content experience is then enhanced by the studentsʼ own direct interaction with and interviewing of women entrepreneurs. The implementation, potential outcomes, and possible adaptations of the course are described, and this transformational learning process model is illustrated.