A New Model to Compute the Information Content of Concepts from Taxonomic Knowledge

2012 ◽  
Vol 8 (2) ◽  
pp. 34-50 ◽  
Author(s):  
David Sánchez ◽  
Montserrat Batet
Keyword(s):  
Information Content ◽  
Semantic Similarity ◽  
Similarity Measures ◽  
New Model ◽  
Amount Of Information ◽  
Data Sparseness ◽  
The Past

The Information Content (IC) of a concept quantifies the amount of information it provides when appearing in a context. In the past, IC used to be computed as a function of concept appearance probabilities in corpora, but corpora-dependency and data sparseness hampered results. Recently, some other authors tried to overcome previous approaches, estimating IC from the knowledge modeled in an ontology. In this paper, the authors develop this idea, by proposing a new model to compute the IC of a concept exploiting the taxonomic knowledge modeled in an ontology. In comparison with related works, their proposal aims to better capture semantic evidences found in the ontology. To test the authors’ approach, they have applied it to well-known semantic similarity measures, which were evaluated using standard benchmarks. Results show that the use of the authors’ model produces, in most cases, more accurate similarity estimations than related works.

scholarly journals Information Content-Based Gene Ontology Semantic Similarity Approaches: Toward a Unified Framework Theory

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Gaston K. Mazandu ◽  
Nicola J. Mulder
Keyword(s):  
Gene Ontology ◽  
Information Content ◽  
Semantic Similarity ◽  
Experimental Evaluation ◽  
Similarity Measures ◽  
Mathematical Framework ◽  
Unified Framework ◽  
The Impact ◽  
Unified Description ◽  
Similarity Scores

Several approaches have been proposed for computing term information content (IC) and semantic similarity scores within the gene ontology (GO) directed acyclic graph (DAG). These approaches contributed to improving protein analyses at the functional level. Considering the recent proliferation of these approaches, a unified theory in a well-defined mathematical framework is necessary in order to provide a theoretical basis for validating these approaches. We review the existing IC-based ontological similarity approaches developed in the context of biomedical and bioinformatics fields to propose a general framework and unified description of all these measures. We have conducted an experimental evaluation to assess the impact of IC approaches, different normalization models, and correction factors on the performance of a functional similarity metric. Results reveal that considering only parents or only children of terms when assessing information content or semantic similarity scores negatively impacts the approach under consideration. This study produces a unified framework for current and future GO semantic similarity measures and provides theoretical basics for comparing different approaches. The experimental evaluation of different approaches based on different term information content models paves the way towards a solution to the issue of scoring a term’s specificity in the GO DAG.

scholarly journals Smart combination of web measures for solving semantic similarity problems

2017 ◽  
Author(s):  
Jorge Martinez‐Gil ◽  
José F. Aldana‐Montes
Keyword(s):  
Data Integration ◽  
Semantic Similarity ◽  
Query Expansion ◽  
Similarity Measures ◽  
Text Clustering ◽  
The Past

Semantic similarity measures are very important in many computer‐related fields. Previous works on applications such as data integration, query expansion, tag refactoring or text clustering have used some semantic similarity measures in the past. Despite the usefulness of semantic similarity measures in these applications, the problem of measuring the similarity between two text expressions remains a key challenge. This paper aims to address this issue.

Dimensi Edukatif pada Kisah-Kisah Al-Qur'an

SUHUF ◽  
2015 ◽  
Vol 3 (1) ◽  
pp. 69-83
Author(s):  
Novita Siswayanti
Keyword(s):  
Teaching Methods ◽  
Religious Values ◽  
Human Beings ◽  
Learning Materials ◽  
Transformative Power ◽  
Amount Of Information ◽  
Vast Amount ◽  
The Past ◽  
Religious Text ◽  
The Future

The stories in Qur'an are Allah’s decrees which convey more beau-tiful values beyond any religious text ever written. It is the holiest scripture and is written  in a wonderful, understandable, and attract-ive language humbly conveying a vast amount of information about life and events that happened in the past. It’s aim is to be an object of reflection for human beings living in this age and the future. Even more so, the stories in Al-Qur'an also entail an educative function providing learning materials,  and teaching methods, regarding the transformative power of Islam and the internalization of true religious values.

The Information Content of Royalty Income

2004 ◽  
Vol 18 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Feng Gu ◽  
Baruch Lev
Keyword(s):  
Information Content ◽  
Intangible Assets ◽  
High Tech ◽  
Patent Licensing ◽  
Financial Reports ◽  
Quarter Century ◽  
Steep Increase ◽  
The Past ◽  
Corporate Growth

The rise of intangible assets in size and contribution to corporate growth over the past quarter century was accompanied by a steep increase in the rate and scope of patenting. Consequently, many patent-rich companies, particularly in the science-based and high-tech industries, are extensively engaged in the licensing and sale of patents. We examine various valuation and disclosure aspects of the outcome of patent licensing—royalty income. Our findings indicate the following: (1) royalty income is highly relevant to securities valuation, (2) the intensity of royalty income provides investors with an important signal about the quality and prospects of firms' R&D expenditures, and (3) a substantial number of companies engaged in patent licensing do not disclose royalty income in financial reports.

Investigation into steering wheel nibble

2002 ◽  
Vol 216 (4) ◽  
pp. 267-277 ◽  
Author(s):  
U Neureder
Keyword(s):  
Design Of Experiments ◽  
Natural Frequency ◽  
Dry Friction ◽  
Parameter Sensitivity ◽  
Steering Wheel ◽  
New Model ◽  
The Past ◽  
Force Variation

Many studies of mechanisms contributing to steering wheel nibble have been carried out in the past. This paper deals with some aspects that have not yet been studied, or those that have been presented by several authors but are deemed to be controversial. Firstly, an overview of stimulation sources (disturbance factors), and the significance these have with respect to steering nibble, is given. As an example of the controversial aspects of the problem, this paper deals with the assumption of dry friction in steering gear models and its conflict with the observed transfer of vibration caused by small (realistic) amounts of imbalance or tyre force variation. After modelling the steering gear resistance correctly, it is possible to identify, in the steering gear, a natural frequency that contributes reasonably to the nibble phenomenon. Based on this new model, a CAE study on parameter sensitivity, using the ‘design of experiments’ approach, is presented.

Denoising distant supervision for ontology lexicalization using semantic similarity measures

2021 ◽  
Vol 177 ◽  
pp. 114922
Author(s):  
Mehdi Jabalameli ◽  
Mohammadali Nematbakhsh ◽  
Reza Ramezani
Keyword(s):  
Semantic Similarity ◽  
Similarity Measures ◽  
Distant Supervision
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