scholarly journals Weisfeiler-Leman in the Bamboo: Novel AMR Graph Metrics and a Benchmark for AMR Graph Similarity

2021 ◽  
Vol 9 ◽  
pp. 1425-1441
Author(s):  
Juri Opitz ◽  
Angel Daza ◽  
Anette Frank
Keyword(s):  
Similarity Metrics ◽  
Stress Tests ◽  
Graph Similarity ◽  
Empirical Assessment ◽  
Graph Transformations ◽  
Graph Metrics ◽  
Sentence Similarity ◽  
Similarity Ratings ◽  
Future Work ◽  
Alignment Step

Abstract Several metrics have been proposed for assessing the similarity of (abstract) meaning representations (AMRs), but little is known about how they relate to human similarity ratings. Moreover, the current metrics have complementary strengths and weaknesses: Some emphasize speed, while others make the alignment of graph structures explicit, at the price of a costly alignment step. In this work we propose new Weisfeiler-Leman AMR similarity metrics that unify the strengths of previous metrics, while mitigating their weaknesses. Specifically, our new metrics are able to match contextualized substructures and induce n:m alignments between their nodes. Furthermore, we introduce a Benchmark for AMR Metrics based on Overt Objectives (Bamboo), the first benchmark to support empirical assessment of graph-based MR similarity metrics. Bamboo maximizes the interpretability of results by defining multiple overt objectives that range from sentence similarity objectives to stress tests that probe a metric’s robustness against meaning-altering and meaning- preserving graph transformations. We show the benefits of Bamboo by profiling previous metrics and our own metrics. Results indicate that our novel metrics may serve as a strong baseline for future work.

Similarity computation using semantic networks created from web-harvested data

2013 ◽  
Vol 21 (1) ◽  
pp. 49-79 ◽  
Author(s):  
ELIAS IOSIF ◽  
ALEXANDROS POTAMIANOS
Keyword(s):  
State Of The Art ◽  
Semantic Network ◽  
Semantic Networks ◽  
Similarity Metrics ◽  
Web Document ◽  
Context Similarity ◽  
Semantic Models ◽  
Similarity Ratings ◽  
Similarity Computation ◽  
Distributional Semantic Models

AbstractWe investigate language-agnostic algorithms for the construction of unsupervised distributional semantic models using web-harvested corpora. Specifically, a corpus is created from web document snippets, and the relevant semantic similarity statistics are encoded in a semantic network. We propose the notion of semantic neighborhoods that are defined using co-occurrence or context similarity features. Three neighborhood-based similarity metrics are proposed, motivated by the hypotheses of attributional and maximum sense similarity. The proposed metrics are evaluated against human similarity ratings achieving state-of-the-art results.

scholarly journals Research of Global Features of 3D Color Histogram with Similarity and Dissimilarity Metrics for Image Processing

2020 ◽  
Vol 9 (3S) ◽  
pp. 359-365
Keyword(s):  
Similarity Score ◽  
Similarity Metrics ◽  
Distance Metrics ◽  
Global Features ◽  
Query Image ◽  
The Third ◽  
Metric Analysis ◽  
Image Library ◽  
Chi Squared ◽  
Future Work

A review of the global feature color comprising of seven different metrics are discussed here. The color is the most powerful feature for describing the images. This study contains four sections. The first section explains the related techniques used in various papers. The second section explains the two different kinds of metrics. (1) Similarity metrics such as Cosine and Correlation and (2) Dissimilarity metrics such as Euclidean, Manhattan, Bhattacharyya, Chi-Squared and Intersection. The third section explains experiment results using CALTECHUCSD Birds-200 image library. The fourth section gives the conclusion and future work. In this experiment, the query image can be divided into trained (indexed) or untrained (non-indexed). In the similarity metric analysis, the experimental results show that the cosine similarity gives better similarity score than correlation. Similarly, in the dissimilarity metric analysis, the Bhattacharyya gives a better result than other distance metrics.

scholarly journals An Exhaustive Survey on Meta-Heuristic Algorithms for Unimodal and Multimodal Optimization

2020 ◽  
Vol 9 (3S) ◽  
pp. 366-372
Keyword(s):  
Heuristic Algorithms ◽  
Similarity Score ◽  
Similarity Metrics ◽  
Distance Metrics ◽  
Multimodal Optimization ◽  
Query Image ◽  
Metric Analysis ◽  
Image Library ◽  
Chi Squared ◽  
Future Work

A review of the global feature color comprising of seven different metrics are discussed here. The color is the most powerful feature for describing the images. This study contains four sections. The first section explains the related techniques used in various papers. The second section explains the two different kinds of metrics. (1) Similarity metrics such as Cosine and Correlation and (2) Dissimilarity metrics such as Euclidean, Manhattan, Bhattacharyya, Chi-Squared and Intersection. The third section explains experiment results using CALTECHUCSD Birds-200 image library. The fourth section gives the conclusion and future work. In this experiment, the query image can be divided into trained (indexed) or untrained (non-indexed). In the similarity metric analysis, the experimental results show that the cosine similarity gives better similarity score than correlation. Similarly, in the dissimilarity metric analysis, the Bhattacharyya gives a better result than other distance metrics.

scholarly journals Visual and Semantic Similarity Norms for a Photographic Image Stimulus Set Containing Recognizable Objects, Animals and Scenes

2021 ◽  
Author(s):  
Zhuohan Jiang ◽  
D. Merika W. Sanders ◽  
Rosemary Cowell
Keyword(s):  
Semantic Similarity ◽  
Conceptual Knowledge ◽  
Stress Tests ◽  
Photographic Images ◽  
Dimensional Scaling ◽  
Outdoor Scenes ◽  
Indoor Scenes ◽  
Similarity Ratings ◽  
Similarity Relationships ◽  
Amazon's Mechanical Turk

We collected visual and semantic similarity norms for a set of photographic images comprising 120 recognizable objects/animals and 120 indoor/outdoor scenes. Human observers rated the similarity of pairs of images within four categories of stimulus ‒ inanimate objects, animals, indoor scenes and outdoor scenes ‒ via Amazon's Mechanical Turk. We performed multi-dimensional scaling (MDS) on the collected similarity ratings to visualize the perceived similarity for each image category, for both visual and semantic ratings. The MDS solutions revealed the expected similarity relationships between images within each category, along with intuitively sensible differences between visual and semantic similarity relationships for each category. Stress tests performed on the MDS solutions indicated that the MDS analyses captured meaningful levels of variance in the similarity data. These stimuli, associated norms and naming data are made publicly available, and should provide a useful resource for researchers of vision, memory and conceptual knowledge wishing to run experiments using well-parameterized stimulus sets.

scholarly journals Evolutionary algorithm based on different semantic similarity functions for synonym recognition in the biomedical domain

2017 ◽  
Author(s):  
José M. Chaves-González ◽  
Jorge Martinez-Gil
Keyword(s):  
Evolutionary Algorithm ◽  
Semantic Similarity ◽  
Pearson Correlation ◽  
Similarity Metrics ◽  
Biomedical Domain ◽  
Similarity Functions ◽  
New Approach ◽  
Domain Specific ◽  
Similarity Ratings ◽  
Very High

One of the most challenging problems in the semantic web field consists of computing the semantic similarity between different terms. The problem here is the lack of accurate domain-specific dictionaries, such as biomedical, financial or any other particular and dynamic field. In this article we propose a new approach which uses different existing semantic similarity methods to obtain precise results in the biomedical domain. Specifically, we have developed an evolutionary algorithm which uses information provided by different semantic similarity metrics. Our results have been validated against a variety of biomedical datasets and different collections of similarity functions. The proposed system provides very high quality results when compared against similarity ratings provided by human experts (in terms of Pearson correlation coefficient) surpassing the results of other relevant works previously published in the literature.

Present status of radio astrometry with baselines ≤ 35 km

1978 ◽  
Vol 48 ◽  
pp. 175-178 ◽  
Author(s):  
K. J. Johnston
Keyword(s):  
Present Status ◽  
Future Work

A summary of results for radio astrometry with baselines ≤ 35 km and priorities for future work are given.

A Phonomotor Approach to Apraxia of Speech Treatment

2020 ◽  
Vol 29 (4) ◽  
pp. 2109-2130
Author(s):  
Lauren Bislick
Keyword(s):  
Phase I ◽  
Treatment Effects ◽  
Single Case ◽  
Motor Planning ◽  
The Other ◽  
Multimodal Approach ◽  
Apraxia Of Speech ◽  
Duration Of Treatment ◽  
Treatment Gains ◽  
Future Work

Purpose This study continued Phase I investigation of a modified Phonomotor Treatment (PMT) Program on motor planning in two individuals with apraxia of speech (AOS) and aphasia and, with support from prior work, refined Phase I methodology for treatment intensity and duration, a measure of communicative participation, and the use of effect size benchmarks specific to AOS. Method A single-case experimental design with multiple baselines across behaviors and participants was used to examine acquisition, generalization, and maintenance of treatment effects 8–10 weeks posttreatment. Treatment was distributed 3 days a week, and duration of treatment was specific to each participant (criterion based). Experimental stimuli consisted of target sounds or clusters embedded nonwords and real words, specific to each participants' deficit. Results Findings show improved repetition accuracy for targets in trained nonwords, generalization to targets in untrained nonwords and real words, and maintenance of treatment effects at 10 weeks posttreatment for one participant and more variable outcomes for the other participant. Conclusions Results indicate that a modified version of PMT can promote generalization and maintenance of treatment gains for trained speech targets via a multimodal approach emphasizing repeated exposure and practice. While these results are promising, the frequent co-occurrence of AOS and aphasia warrants a treatment that addresses both motor planning and linguistic deficits. Thus, the application of traditional PMT with participant-specific modifications for AOS embedded into the treatment program may be a more effective approach. Future work will continue to examine and maximize improvements in motor planning, while also treating anomia in aphasia.

Confirmatory Factor Analysis of the Long and Short Forms of the Worry Domains Questionnaire

2009 ◽  
Vol 25 (4) ◽  
pp. 239-243
Author(s):  
Roberto Nuevo ◽  
Andrés Losada ◽  
María Márquez-González ◽  
Cecilia Peñacoba
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Factor Structure ◽  
Goodness Of Fit ◽  
Factorial Validity ◽  
Fit Indices ◽  
Short Forms ◽  
Confirmatory Factor ◽  
Positive Correlations ◽  
Future Work

The Worry Domains Questionnaire was proposed as a measure of both pathological and nonpathological worry, and assesses the frequency of worrying about five different domains: relationships, lack of confidence, aimless future, work, and financial. The present study analyzed the factor structure of the long and short forms of the WDQ (WDQ and WDQ-SF, respectively) through confirmatory factor analysis in a sample of 262 students (M age = 21.8; SD = 2.6; 86.3% females). While the goodness-of-fit indices did not provide support for the WDQ, good fit indices were found for the WDQ-SF. Furthermore, no source of misspecification was identified, thus, supporting the factorial validity of the WDQ-SF scale. Significant positive correlations between the WDQ-SF and its subscales with worry (PSWQ), anxiety (STAI-T), and depression (BDI) were found. The internal consistency was good for the total scale and for the subscales. This work provides support for the use of the WDQ-SF, and potential uses for research and clinical purposes are discussed.

Psychology in Outerspace

2010 ◽  
Vol 15 (3) ◽  
pp. 220-228 ◽  
Author(s):  
Viren Swami ◽  
Tomas Chamorro-Premuzic ◽  
Manal Shafi
Keyword(s):  
Individual Difference ◽  
Sensation Seeking ◽  
Structural Equation ◽  
Political Orientation ◽  
Equation Modeling ◽  
Big Five Personality ◽  
Social Conformity ◽  
Extraterrestrial Life ◽  
Paranormal Beliefs ◽  
Future Work

Previous work has shown that is important to consider the disjunction between paranormal and nonparanormal beliefs about extraterrestrial life. The current study examined the association between both such beliefs and individual difference and demographic variables. A total of 555 British participants completed the Extraterrestrial Beliefs Scale, as well as measures of their Big Five personality scores, social conformity, sensation seeking, and demographics. Results showed no sex differences in ratings of paranormal and nonparanormal extraterrestrial beliefs, but participants rated nonparanormal beliefs more positively than paranormal beliefs. Results of structural equation modeling showed that individual difference factors (specifically, Openness, Conscientiousness, and social conformity) explained 21% of the variance in extraterrestrial beliefs, whereas demographic factors (specifically, education level, political orientation, and religiosity) explained 16% of the variance. Limitations and directions for future work are considered.

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