An Ontology-driven Document Retrieval Strategy for Organizational Knowledge Management Systems

Toledo, Carlos M.; Ale, Mariel Alejandra; Chiotti, Omar; Galli, Marı́a Rosa

doi:10.1016/j.entcs.2011.11.023

Cited by 16 publications

(6 citation statements)

References 9 publications

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“…These relationships are fluid; for example, using the same Pokémon with a different item may change its relationships to its teammates. Ontologies have been used extensively to store knowledge in a format that encourages complex relationships between entities (Niaraki and Kim 2009;Toledo et al 2011). These techniques have not been introduced to any esports context, but the complexity of most competitive video games lends itself to the strength of ontological modeling.…”

Section: Related Workmentioning

confidence: 99%

Ontology-based Knowledge System and Team Verification Tool for Competitive Pokemon

Verdear

Visser²

2021

FLAIRS

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Competitive Pokemon is a domain with rich semantics and complex relationships between its elements. Current research in the domain has focused on developing AI agents to select moves within a match, ignoring the problem of team building. We propose a team verification tool based on ontologies to model the complexities of the domain. A user can input their team into the tool, and the tool uses a description logic reasoner to classify Pokemon into their appropriate roles. The tool exports a visual representation of the team and a score evaluating its competitive viability. The classifications made by the TeamVerify tool have 87.7% precision and 86.0% recall in a multiclass, multilabel domain. We expect such a tool to reduce the learning curve for novice players who have not yet built intuitions on proper team structure.

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Section: Related Workmentioning

confidence: 99%

Ontology-based Knowledge System and Team Verification Tool for Competitive Pokemon

Verdear

Visser²

2021

FLAIRS

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“…This study (Chen, 2008) combines swarm intelligence and Web Services to transform a conventional library system into an intelligent library system with high integrity, usability, correctness, and reliability software for readers. This research (Toledo, 2011) proposes organizational memory architecture, and annotation strategies based on domain ontologies to retrieve information through natural language queries. Although search engines have developed effective searches, information overload obstructs precise searches.…”

Section: Introductionmentioning

confidence: 99%

Improving Knowledge Retrieval in Digital Libraries Applying Intelligent Techniques

Martín

León

2014

Proceedings of the International Conference on Knowledge Engineering and Ontology Development

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Nowadays an enormous quantity of heterogeneous and distributed information is stored in the digital University. Exploring online collections to find knowledge relevant to a user's interests is a challenging work. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. In this work we propose a comprehensive approach for discovering E-learning objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We have used Case Based-Reasoning methodology to develop a prototype for supporting efficient retrieval knowledge from online repositories. We suggest a conceptual architecture for a semantic search engine. OntoUS is a collaborative effort that proposes a new form of interaction between users and digital libraries, where the latter are adapted to users and their surroundings.

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“…We could identify four approaches (Han and Park, 2009;Holz et al, 2005;Kankanhalli et al, 2011;Toledo et al, 2011), with only two Recognizing learnings from OMIS research of them being relevant for analyzing KMISs with external user context, namely, Holz et al (2005) and Toledo et al (2011). From these two, we finally selected the one of assumable higher scientific relevance (measured by the impact factor of the publishing journal).…”

Section: Case Selectionmentioning

confidence: 99%

“…From these two, we finally selected the one of assumable higher scientific relevance (measured by the impact factor of the publishing journal). The approach by Toledo et al (2011) was published in 2011 and represents a typical approach for a KMS with external user context. 5.2.3 Case 3 (product-based, heavy-weight).…”

Section: Case Selectionmentioning

confidence: 99%

“…Research has focused on the opportunities for organizational stakeholders to use existing information, therefore pursuing similar objectives as KMSs. Research under the OMIS label is usually linked to adopting a socio-technical perspective on knowledge use and sharing in actual work situations (Ackerman and Halverson, 2004;Ackerman et al, 2013b), while KMSs research usually adopts a more techno-centric perspective on knowledge storage and retrieval (Toledo et al, 2011;Zhang et al, 2011) and often does not explicitly consider the social and organizational context of knowledge delivery.…”

Section: Introductionmentioning

confidence: 99%

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KMS re-contextualization – recognizing learnings from OMIS research

Mühlburger

Oppl

Stary

2017

VJIKMS

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Purpose Deployment of knowledge management systems (KMSs) suffers from low adoption in organizational reality that is attributed to a lack of perceivable added value for people in actual work situations. Poor task/technology fit in the process of knowledge retrieval appears to be a major factor influencing this issue. Existing research indicates a lack of re-contextualizing stored information provided by KMSs in a particular situation. Existing research in the area of organizational memory information systems (OMISs) has thoroughly examined and widely discussed the topic of re-contextualization. The purpose of this paper, thus, is to examine how KMS design can benefit from OMIS research on approaches for re-contextualization in knowledge retrieval. Design/methodology/approach This paper examines OMIS literature and inductively derives a categorization scheme for KMS according to their strategy of re-contextualizing knowledge. The authors have validated the scheme validated in a multiple case study that examines the differentiatory value of the scheme for approaches with various re-contextualization strategies. Findings The classification scheme allows a step-by-step selection of approaches for re-contextualization of information in KMS design and development derived from OMIS research. The case study has demonstrated the applicability of the developed scheme and shows that the differentiation criteria can be applied unambiguously. Research limitations/implications Because of the chosen case study approach for validation, the validation results may lack generalizability. Practical implications The scheme enables an informed selection of KMSs appropriate for a particular OMIS use case, as the scheme’s attributes serve as design rationale for a certain architecture or constellation of components. Developers can not only select from various approaches when designing re-contextualizaton but also come up with rationales for each candidate because of structured representation. Hence, stakeholders can be supported in a more informed way and design KMSs more effectively along organizational change processes. Originality/value The paper addresses an identified need for systematic characterization of KMS approaches and systems intending to meet the objectives of OMISs. As such, it allows streamlining further research in this field, as approaches can be judged according to their originality and positioned relative to each other.

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An Ontology-driven Document Retrieval Strategy for Organizational Knowledge Management Systems

Cited by 16 publications

References 9 publications

Ontology-based Knowledge System and Team Verification Tool for Competitive Pokemon

Ontology-based Knowledge System and Team Verification Tool for Competitive Pokemon

Improving Knowledge Retrieval in Digital Libraries Applying Intelligent Techniques

KMS re-contextualization – recognizing learnings from OMIS research

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