Incremental Knowledge Base Construction Using DeepDive

Populating a database with unstructured information is a long-standing problem in industry and research that encompasses problems of extraction, cleaning, and integration. Recent names used for this problem include dealing with dark data and knowledge base construction (KBC). In this work, we describe DeepDive, a system that combines database and machine learning ideas to help develop KBC systems, and we present techniques to make the KBC process more efficient. We observe that the KBC process is iterative, and we develop techniques to incrementally produce inference results for KBC systems. We propose two methods for incremental inference, based respectively on sampling and variational techniques. We also study the tradeoff space of these methods and develop a simple rule-based optimizer. DeepDive includes all of these contributions, and we evaluate DeepDive on five KBC systems, showing that it can speed up KBC inference tasks by up to two orders of magnitude with negligible impact on quality

Fostering collaborative knowledge construction with visualization tools

This study investigates to what extent collaborative knowledge construction can be fostered by providing students with visualization tools as structural support. Thirty-two students of Educational Psychology took part in the study. The students were subdivided into dyads and asked to solve a case problem of their learning domain under one of two conditions: 1) with content-specific visualization 2) with content-unspecific visualization. Results show that by being provided with a content-specific visualization tool, both the process and the outcome of the cooperative effort improved. More specifically, dyads under that condition referred to more adequate concepts, risked more conflicts, and were more successful in integrating prior knowledge into the collaborative solution. Moreover, those learning partners had a more similar individual learning outcome

Managing knowledge in the context of sustainable construction

The 21st century has been a growing awareness of the importance of the sustainability agenda. Moreover for construction, it has become increasingly important as clients are pushing for a more sustainable product to complement their organisations’ own strategic plans. Sustainable development can be defined as development that meets the needs of the present without compromising the ability of future generations to meet their needs. Sustainable construction is therefore seen as the application of sustainable practices to the activities of the construction sector. One of the key factors in making construction projects more sustainable is overcoming the obstacles of capturing and managing the knowledge required by project teams to effect such change. Managing this knowledge is key to the construction industry because of the unique characteristics of its projects, i.e. multi-disciplinary teams, dynamic participation of team members, heavy reliance on previous experiences/heuristics, the one-off nature of the projects, tight schedules, limited budget, etc. Initiatives within the industry and academic research are developing mechanisms and tools for managing knowledge in construction firms and projects. Such work has so far addressed the issues of capturing, storing, and transferring knowledge

NOUS: Construction and Querying of Dynamic Knowledge Graphs

The ability to construct domain specific knowledge graphs (KG) and perform question-answering or hypothesis generation is a transformative capability. Despite their value, automated construction of knowledge graphs remains an expensive technical challenge that is beyond the reach for most enterprises and academic institutions. We propose an end-to-end framework for developing custom knowledge graph driven analytics for arbitrary application domains. The uniqueness of our system lies A) in its combination of curated KGs along with knowledge extracted from unstructured text, B) support for advanced trending and explanatory questions on a dynamic KG, and C) the ability to answer queries where the answer is embedded across multiple data sources.Comment: Codebase: https://github.com/streaming-graphs/NOU

Managing the construction worker in a knowledge environment

Valuable human and knowledge resources will be wasted unless organisations make better use of these prime resources. Construction knowledge workers and their tacit knowledge in particular is still considered to be relatively unexplored and proper understanding and management of this resource is of immense importance for better organisational performance. The paper stresses the importance of knowledge worker and tacit knowledge in construction and examines the contribution towards the company performance. Two dimensions in construction knowledge worker management are highlighted. This provides a valid basis to embrace the concept of knowledge worker and a knowledge culture at all levels within construction organisations