Semantic relations in information science

Khoo, Christopher S. G.; Na, Jin‐Cheon

doi:10.1002/aris.1440400112

Cited by 92 publications

(92 citation statements)

References 238 publications

(302 reference statements)

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“…it is influenced by culture and educational background. As stated previously, prior research has shown a significant cross-cultural overlap [29], [30], [31], [32], [33], [34] on the relatedness ratings of certain kinds of semantic knowledge. Relations between most natural, physical and biological concepts, e.g.…”

Section: Measurement Processesmentioning

confidence: 91%

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ZeTA-Zero-Trust Authentication: Relying on Innate Human Ability, Not Technology

Gutmann

Renaud

Maguire

et al. 2016

2016 IEEE European Symposium on Security and Privacy (EuroS&P)

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Abstract-Reliable authentication requires the devices and channels involved in the process to be trustworthy; otherwise authentication secrets can easily be compromised. Given the unceasing efforts of attackers worldwide such trustworthiness is increasingly not a given. A variety of technical solutions, such as utilising multiple devices/channels and verification protocols, has the potential to mitigate the threat of untrusted communications to a certain extent. Yet such technical solutions make two assumptions: (1) users have access to multiple devices and (2) attackers will not resort to hacking the human, using social engineering techniques. In this paper, we propose and explore the potential of using human-based computation instead of solely technical solutions to mitigate the threat of untrusted devices and channels. ZeTA (Zero Trust Authentication on untrusted channels) has the potential to allow people to authenticate despite compromised channels or communications and easily observed usage. Our contributions are threefold: (1) We propose the ZeTA protocol with a formal definition and security analysis that utilises semantics and human-based computation to ameliorate the problem of untrusted devices and channels. (2) We outline a security analysis to assess the envisaged performance of the proposed authentication protocol. (3) We report on a usability study that explores the viability of relying on human computation in this context.

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Section: Measurement Processesmentioning

confidence: 91%

“…One of the main advantages in using human processing is that much of the knowledge stored in semantic memory has a high inter-human correlation, i.e. a large fraction of this knowledge is consistent among most people [29], [30], [31], [32], [33], [34].…”

Section: Pre-considerations and High-level Descriptionmentioning

confidence: 99%

ZeTA-Zero-Trust Authentication: Relying on Innate Human Ability, Not Technology

Gutmann

Renaud

Maguire

et al. 2016

2016 IEEE European Symposium on Security and Privacy (EuroS&P)

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“…However, this is not the only issue. In their review of semantic relations in information science Khoo et al (2006) concluded that "no systematic analysis of the type of semantic relations used in ontologies has been reported in the literature." One implication of this conclusion is that there is no easy way of verifying whether the type of ontology or knowledge base that would contain the relations that are of interest to researchers in specialized domains already exists.…”

Section: Related Workmentioning

confidence: 99%

“…Although precoordinated indexing (an example is the Library of Congress Subject Headings) has supported associations between index terms as far back as 1967, Farradane pointed out that such implied relations expressed through precoordinated indexing are unambiguous only in a narrow domain (Khoo et al, 2006). Automated relation extraction is an active area of research (Moldovan, 2000;Khoo et al, 2006;Frunza et al, 2011;Arighi et al, 2013, Konstantinova, 2014 and approaches tend to cluster around two different strategies. At one end of the spectrum are the domain specific relations that operate over particular entities, as is typified in biomedicine where gene-protein or protein-locations (Kim et al, 2003) have been well explored.…”

Section: Introductionmentioning

confidence: 99%

Learning user‐defined, domain‐specific relations: A situated case study and evaluation in plant science

Lučić

Blake

2015

Proc. Assoc. Info. Sci. Tech.

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Although methods exist to identify well-defined relations, such as is_a or part_of, existing tools rarely support a user who wants to define new, domain-specific relations. We conducted a situated case study in plant science and introduce four new domain-specific relations that are of interest to domain scientists but have not been explored in information science. Results show that precision varies between relations and ranges from 0.73 to 0.91 for the manufacturer location category, 0.89 and 0.93 for the seed donor-bank relation, 0.29 and 0.67 for the seed origin location, and 0.32 and 0.77 for the field experiment location. The manufacturer location category recall varies from 0.91 to 0.94, the seed bank-donor location recall ranges between 0.93 and 1, the seed origin relation from 0.33 to 0.82 while the field experiment location from 0.67 to 0.83 depending on the classifier and using a combination of lexical and syntactic features in the background.

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“…Recognition [4], Semantic Role Identification [5], and Relation Extraction [6], [7]. Considering technology as applied science, then scientific publications can be considered as a primary source of information about technologies and emerging technological trends.…”

Section: Introductionmentioning

confidence: 99%

Towards Technology Structure Mining from Scientific Literature

QasemiZadeh

2010

Lecture Notes in Computer Science

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Abstract. This paper introduces the task of Technology-Structure Mining to support Management of Technology. We propose a linguistic based approach for identification of Technology Interdependence through extraction of technology concepts and relations between them. In addition, we introduce Technology Structure Graph for the task formalization. While the major challenge in technology structure mining is the lack of a benchmark dataset for evaluation and development purposes, we describes steps that we have taken towards providing such a benchmark. The proposed approach is initially evaluated and applied in the domain of Human Language Technology and primarily results are demonstrated. We further explain plans and research challenges for evaluation of the proposed task.

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Semantic relations in information science

Cited by 92 publications

References 238 publications

ZeTA-Zero-Trust Authentication: Relying on Innate Human Ability, Not Technology

ZeTA-Zero-Trust Authentication: Relying on Innate Human Ability, Not Technology

Learning user‐defined, domain‐specific relations: A situated case study and evaluation in plant science

Towards Technology Structure Mining from Scientific Literature

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