Bio-ontologies are essential tools for accessing and analyzing the rapidly growing pool of plant genomic and phenomic data. Ontologies provide structured vocabularies to support consistent aggregation of data and a semantic framework for automated analyses and reasoning. They are a key component of the Semantic Web. This paper provides background on what bio-ontologies are, why they are relevant to botany, and the principles of ontology development. It includes an overview of ontologies and related resources that are relevant to plant science, (...) with a detailed description of the Plant Ontology (PO). We discuss the challenges of building an ontology that covers all green plants (Viridiplantae). Key results: Ontologies can advance plant science in four keys areas: 1. comparative genetics, genomics, phenomics, and development, 2. taxonomy and systematics, 3. semantic applications and 4. education. Conclusions: Bio-ontologies offer a flexible framework for comparative plant biology, based on common botanical understanding. As genomic and phenomic data become available for more species, we anticipate that the annotation of data with ontology terms will become less centralized, while at the same time, the need for cross-species queries will become more common, causing more researchers in plant science to turn to ontologies. (shrink)

Since Turing proposed the first test of intelligence, several modifications have been proposed with the aim of making Turing’s proposal more realistic and applicable in the search for artificial intelligence. In the modern context, it turns out that some of these definitions of intelligence and the corresponding tests merely measure computational power. Furthermore, in the framework of the original Turing test, for a system to prove itself to be intelligent, a certain amount of deceit is implicitly required which can have (...) serious security implications for future human societies. In this article, we propose a unified framework for developing intelligence tests which takes care of important ethical and practical issues. Our proposed framework has several important consequences. Firstly, it results in the suggestion that it is not possible to construct a single, context independent, intelligence test. Secondly, any measure of intelligence must have access to the process by which a problem is solved by the system under consideration and not merely the final solution. Finally, it requires an intelligent agent to be evolutionary in nature with the flexibility to explore new algorithms on its own. (shrink)

In this paper, we employ bibliometric analysis to empirically analyse the research on social entrepreneurship published between 1996 and 2017. By employing methods of citation analysis, document co-citation analysis, and social network analysis, we analyse 1296 papers containing 74,237 cited references and uncover the structure, or intellectual base, of research on social entrepreneurship. We identify nine distinct clusters of social entrepreneurship research that depict the intellectual structure of the field. The results provide an overall perspective of the social entrepreneurship field, (...) identifying its influential works and analysing scholarly communication between these works. The results further aid in clarifying the overall centrality features of the social entrepreneurship research network. We also examine the integration of ethics into social entrepreneurship literature. We conclude with a discussion on the structure and evolution of the social entrepreneurship field. (shrink)

In this paper we take a fresh look at the information retrieval problem of balancing recall with precision in electronic document extraction. We examine the IR constructs of uncertainty, context and relevance, proposing a new process model for context learning, and introducing a new IT artifact designed to support user driven learning by leveraging explicit knowledge to discover implicit knowledge within a corpus of documents. The IT artifact is a prototype designed to present a small set of extracted documents from (...) a targeted corpus based upon user inputted criteria. The prototype provides the user with the opportunity to balance exploration and exploitation, via iterative relevance feedback to address the problem of imprecision resulting from uncertainty. We model the problem as an exploration–exploitation dilemma and apply it to a specific case of IR called eDiscovery. We conduct a series of behavioral experiments to evaluate the model and the artifact. Our initial findings indicate that the proposed model and the artifact improve performance in the IR result. (shrink)

Coreference resolution is a challenging natural language processing task, and it is difficult to identify the correct mentions of an entity that can be any noun or noun phrase. In this article, a semisupervised, two-stage pattern-based bootstrapping approach is proposed for the coreference resolution task. During Stage 1, the possible mentions are identified using word-based features, and during Stage 2, the correct mentions are identified by filtering the non-coreferents of an entity using statistical measures and graph-based features. Whereas the existing (...) approaches use morphosyntactic and number/gender agreement features, the proposed approach uses semantic graph-based context-level semantics and nested noun phrases in the correct mentions identification. Moreover, mentions without the number/gender information are identified, using the context-based features of the semantic graph. The evaluation performed for the coreference resolution shows significant improvements, when compared with the word association-based bootstrapping systems. (shrink)

Post-globalization trends have left many people with a sense of insecurity—on both the economic and the employment fronts. Business re-engineering, downsizing, lay-offs, excessive consumerism and greed have altered the rules of the business game. Skewed attention to mere economic criteria in many business organizations, even at the cost of societal and environmental factors, is leading to a sense of hollowness, ‘something missing’, in the organization and its employees. People are making every attempt to discover this ‘missing component’ in their lives, (...) with particular reference to their work lives. This ‘missing component’ is referred to as ‘spirit at work’ in management literature. Bringing in spirit at work has become a matter of priority for many business organizations, in their drives for sustained success. Spirit at work is about care, compassion, integrity, and about attempting to live one’s values at the workplace. It is about employees who are passionate and energized by their work, who find meaning and purpose and pursue excellence in their work, and who feel that they can express their complete selves at work. It is about individuals and organizations that see work as an opportunity to grow and to contribute to society in a meaningful way. Spirit at work can be better understood by gaining clarity about the key aspects that constitute this concept. This article reviews the extant litera-ture on spirit at work, highlights the key dimensions of spirit at work, and elaborates on each of them. A number of Indian scholars like S.K. Chakraborty, Subhash Sharma, M.B. Athreya, Panduranga Bhatta and others have proposed an Indian perspective of spirit at work and have elaborated on it since a decade and a half. This article extends the Indian perspective further, based on Indian psychophilosophy, and establishes its comprehensive and inclusive nature that enables incorporation of most of the key dimensions of spirit at work as identified in literature. (shrink)