Contextualized Knowledge-aware Attentive Neural Network: Enhancing Answer Selection with Knowledge

Answer selection, which is involved in many natural language processing applications, such as dialog systems and question answering (QA), is an important yet challenging task in practice, since conventional methods typically suffer from the issues of ignoring diverse real-world background knowledge. In this article, we extensively investigate approaches to enhancing the answer selection model with external knowledge from knowledge graph (KG). First, we present a context-knowledge interaction learning framework, Knowledge-aware Neural Network, which learns the QA sentence representations by considering a tight interaction with the external knowledge from KG and the textual information. Then, we develop two kinds of knowledge-aware attention mechanism to summarize both the context-based and knowledge-based interactions between questions and answers. To handle the diversity and complexity of KG information, we further propose a Contextualized Knowledge-aware Attentive Neural Network, which improves the knowledge representation learning with structure information via a customized Graph Convolutional Network and comprehensively learns context-based and knowledge-based sentence representation via the multi-view knowledge-aware attention mechanism. We evaluate our method on four widely used benchmark QA datasets, including WikiQA, TREC QA, InsuranceQA, and Yahoo QA. Results verify the benefits of incorporating external knowledge from KG and show the robust superiority and extensive applicability of our method.

Unstructured Text Enhanced Open-Domain Dialogue System: A Systematic Survey

Incorporating external knowledge into dialogue generation has been proven to benefit the performance of an open-domain Dialogue System (DS), such as generating informative or stylized responses, controlling conversation topics. In this article, we study the open-domain DS that uses unstructured text as external knowledge sources ( U nstructured T ext E nhanced D ialogue S ystem ( UTEDS )). The existence of unstructured text entails distinctions between UTEDS and traditional data-driven DS and we aim at analyzing these differences. We first give the definition of the UTEDS related concepts, then summarize the recently released datasets and models. We categorize UTEDS into Retrieval and Generative models and introduce them from the perspective of model components. The retrieval models consist of Fusion, Matching, and Ranking modules, while the generative models comprise Dialogue and Knowledge Encoding, Knowledge Selection (KS), and Response Generation modules. We further summarize the evaluation methods utilized in UTEDS and analyze the current models’ performance. At last, we discuss the future development trends of UTEDS, hoping to inspire new research in this field.

Operating Successfully on a New Technological Path: The Effect of External Search

Switching to a new technological path is often a serious economic challenge for companies. Incumbents, in particular, are often led by their organizational routines, traditional technological orientation, and experience, and run the risk of losing contact with new technologies, which can decrease their competitiveness. We analyze whether opening up the innovation process to external knowledge partners can help to overcome such path dependence and enable firms to operate successfully on a new technological path. We develop a theoretical concept that shows the potential of external knowledge sources for operating successfully on a new technological path and test it empirically using the example of green technologies. Green technologies are not only relevant for addressing the current environmental problems, but they are also an example of a new technological path that is proving difficult for companies to switch to. Overall, we find strong direct effects of external (green) knowledge on green innovation success. The results even indicate that the direct effect of external knowledge tends to be larger for green than for non-green innovation.

A Critical Review of Organizing Knowledge Management for Innovation

This study critically reviews the literature that demonstrates the relevance of knowledge management process and business intelligence, as well as the challenges arising when it comes to organising for innovation in today’s business organisations. Hence, the to attain desired innovation it is important to integrate business intelligence (BI) and knowledge management (KM) for the diffusion of innovation. Hence, importance of integrating business intelligence (BI) and knowledge management (KM) for the diffusion of innovation. Organisations’ innovation dynamics and knowledge processes that lead competitive advantage of organisations are examined. Literature points that many organisations rely on individual employees’ knowledge and skills. As a result, information systems that enable knowledge management (KM) as a critical tool for gaining a competitive advantage (Campbell, 2012). The seminal argument in this study is that knowledge diffusion and knowledge externalities are the main drive of increase in economy. As a result, this is expected to be a win-win value proposition for such organisations integrating business intelligence and knowledge management. However, owing to changing business conditions and the rapidity of technological development, as well as the rising expenses involved with carrying out R&D operations in many of these organisations, maintaining competitive advantage through internal R&D alone is becoming increasingly challenging. The importance of innovation processes and network dynamics in the context of Integrated Knowledge Networks is explored, which provide feasible possibilities for utilising innovation as an interactive process as well as knowledge processes for creating business intelligence in organisations. Due to the challenges of organising for innovation, the organisations figured to rely on “Open innovation” approach to intentionally seek out unique knowledge and information outside of their organisational bounds. This study also discusses the challenges that organisations hurdle on in managing inter-organizational cooperation because of external knowledge sourcing techniques (Campbell, 2009). This is due, in part, to the fact that they span a wide range of organisations, people, and resources, as well as the interactions that exist between them. The creative processes and network dynamics are facilitated by an architecture that blends organisational and technical aspects in Integrated Knowledge Networks. Hence, the study focuses on twofold to sourcing external knowledge in particular: learning from international business environments and corporate venturing strategy for corporate incubators.

Family farm succession: evidence from absorptive capacity, social capital, and socioeconomic aspects

Farm succession is a process socially built from the preparation of the successor and the farm to meet a family business’ expectations. This study aimed to identify how social capital, absorptive capacity, and socioeconomic characteristics influence farm succession. The survey was conducted sampling 82 soybean and corn Brazilian farmers. The questionnaire measured socioeconomic characteristics, Absorptive Capacity (AC), and Social Capital (SC). To test the influence of AC, SC, and socioeconomic characteristics on farm succession, Spearman correlation coefficient (rs) was performed. Results showed that the absorptive capacity can influence farm succession through acquisition, assimilation, use, and transformation of external knowledge into decision making, supporting the definition of successors. Results also suggested that social capital plays an important role to form relationship networks, stimulating discussions, and supporting the designation of successors. The socioeconomic characteristics ‘percentage of family income from the farm, participation in courses and lectures, and being a cooperatives member’ also presented a significant positive correlation with farm succession. Issues related to the capacity to absorb external knowledge, social and symbolic capital and generational transference can be fundamental in the continuity of the family farming business.