Semantic composition of AT-LOCATION relation with other relations

2011 ◽  
Vol 18 (3) ◽  
pp. 343-374
Author(s):  
HAKKI C. CANKAYA ◽  
EDUARDO BLANCO ◽  
DAN MOLDOVAN
Keyword(s):  
Experimental Study ◽  
High Accuracy ◽  
Semantic Relations ◽  
Semantic Composition

AbstractThis paper presents a method for the composition of at-location with other semantic relations. The method is based on inference axioms that combine two semantic relations yielding another relation that otherwise is not expressed. An experimental study conducted on PropBank, WordNet, and eXtended WordNet shows that inferences have high accuracy. The method is applicable to combining other semantic relations and it is beneficial to many semantically intense applications.

scholarly journals Word Embedding for Semantically Relative Words: an Experimental Study

2018 ◽  
Vol 25 (6) ◽  
pp. 726-733
Author(s):  
Maria S. Karyaeva ◽  
Pavel I. Braslavski ◽  
Valery A. Sokolov
Keyword(s):  
Experimental Study ◽  
Natural Language Processing ◽  
Language Processing ◽  
Intelligent Systems ◽  
Russian Language ◽  
Word Embedding ◽  
Semantic Relations ◽  
Automatic Extraction ◽  
Semantic Relationships ◽  
The Russian Language

The ability to identify semantic relations between words has made a word2vec model widely used in NLP tasks. The idea of word2vec is based on a simple rule that a higher similarity can be reached if two words have a similar context. Each word can be represented as a vector, so the closest coordinates of vectors can be interpreted as similar words. It allows to establish semantic relations (synonymy, relations of hypernymy and hyponymy and other semantic relations) by applying an automatic extraction. The extraction of semantic relations by hand is considered as a time-consuming and biased task, requiring a large amount of time and some help of experts. Unfortunately, the word2vec model provides an associative list of words which does not consist of relative words only. In this paper, we show some additional criteria that may be applicable to solve this problem. Observations and experiments with well-known characteristics, such as word frequency, a position in an associative list, might be useful for improving results for the task of extraction of semantic relations for the Russian language by using word embedding. In the experiments, the word2vec model trained on the Flibusta and pairs from Wiktionary are used as examples with semantic relationships. Semantically related words are applicable to thesauri, ontologies and intelligent systems for natural language processing.

Readers’ Perceptions of Lexical Cohesion in Text

2013 ◽  
Author(s):  
Jane Morris
Keyword(s):  
Experimental Study ◽  
Individual Differences ◽  
Common Core ◽  
Etude Expérimentale ◽  
Semantic Relations ◽  
Lexical Resources ◽  
Lexical Cohesion ◽  
Preliminary Results ◽  
Lexical Semantic ◽  
Étude Expérimentale

Preliminary results from an experimental study of readers’ perceptions of lexical cohesion and lexical semantic relations in text are presented. Readers agree on a common “core” of groups of related words and exhibit individual differences. The majority of relations reported are “non-classical” (not hyponymy, meronymy, synonymy, or antonymy). A group of commonly used relations is presented. These preliminary results indicate potential for improving both relations existing in lexical resources, and methods dependent on lexical cohesion analysis.Les résultatspréliminaires d’une étude expérimentale sur les perceptions des lecteurs au sujet de la cohésion lexicale et des relations lexicales sémantiques de textes sont présentés. Les lecteurs s’entendent sur un « noyau » commun de groupes de mots reliés et présentent des différences individuelles. La majorité des relations indiquées sont « non classiques » (ni hyponymiques, méronymiques, synonymiques ou antonymiques). Un groupe de relations couramment utilisées est présenté. Ces résultats préliminaires indiquent le potentiel nécessaire pour améliorer aussi bien les relations existant dans les ressources lexicales que les méthodes dépendant de l’analyse de la cohésion lexicale. 

scholarly journals Domain and Function: A Dual-Space Model of Semantic Relations and Compositions

2012 ◽  
Vol 44 ◽  
pp. 533-585 ◽  
Author(s):  
P. D. Turney
Keyword(s):  
Vector Space ◽  
Dual Space ◽  
Vector Space Model ◽  
Semantic Relations ◽  
Semantic Composition ◽  
Space Model ◽  
Function Similarity ◽  
And Function ◽  
Domain Similarity

Given appropriate representations of the semantic relations between carpenter and wood and between mason and stone (for example, vectors in a vector space model), a suitable algorithm should be able to recognize that these relations are highly similar (carpenter is to wood as mason is to stone; the relations are analogous). Likewise, with representations of dog, house, and kennel, an algorithm should be able to recognize that the semantic composition of dog and house, dog house, is highly similar to kennel (dog house and kennel are synonymous). It seems that these two tasks, recognizing relations and compositions, are closely connected. However, up to now, the best models for relations are significantly different from the best models for compositions. In this paper, we introduce a dual-space model that unifies these two tasks. This model matches the performance of the best previous models for relations and compositions. The dual-space model consists of a space for measuring domain similarity and a space for measuring function similarity. Carpenter and wood share the same domain, the domain of carpentry. Mason and stone share the same domain, the domain of masonry. Carpenter and mason share the same function, the function of artisans. Wood and stone share the same function, the function of materials. In the composition dog house, kennel has some domain overlap with both dog and house (the domains of pets and buildings). The function of kennel is similar to the function of house (the function of shelters). By combining domain and function similarities in various ways, we can model relations, compositions, and other aspects of semantics.

Extracting Commonsense Knowledge Using Concepts Properties

2012 ◽  
pp. 341-353
Author(s):  
Eduardo Blanco ◽  
Hakki C. Cankaya ◽  
Dan Moldovan
Keyword(s):  
Semantic Representation ◽  
High Accuracy ◽  
Experimental Results ◽  
Human Interaction ◽  
Semantic Relations ◽  
Commonsense Knowledge ◽  
Novel Method ◽  
Basic Semantic

Commonsense knowledge encompasses facts that people know but do not communicate most of the time. For example, one needs water and soap to take a shower is commonsense. This chapter presents a semantically grounded method for extracting commonsense knowledge. First, commonsense rules are identified, e.g., one cannot see imaginary objects. Second, those rules are combined with a basic semantic representation in order to infer commonsense facts, e.g. one cannot see a flying carpet. Further combinations of semantic relations with inferred commonsense facts are proposed and analyzed. Experimental results show that this novel method is able to extract thousands of commonsense facts with little human interaction and high accuracy.

Study on the Ductile-Mode Milling of Brittle Ceramics

2012 ◽  
Vol 490-495 ◽  
pp. 3654-3657
Author(s):  
Xiang Cheng ◽  
Bin Gao ◽  
Jun Ying Liu ◽  
Xian Hai Yang
Keyword(s):  
Experimental Study ◽  
Brittle Materials ◽  
Ceramic Materials ◽  
High Accuracy ◽  
Experimental Results ◽  
Machining Parameters ◽  
Machining Conditions ◽  
Ductile Mode ◽  
Hard And Brittle Materials ◽  
Experimental Background

Hard and brittle materials such as silicon and ceramic materials are difficult to machining due to their brittle properties. By the ductile-mode machining, delicate features with high accuracy can be created on these materials by mechanical micro/nano machining. This paper introduced the experimental study on the ductile-mode milling of ceramics. First, the experimental background and plans have been introduced. Then, on the sub-micron milling center, experimental results show that ductile-mode machining can be achieved. Both machining parameters and machining conditions are very important in order to realize the ductile-mode machining

scholarly journals Comparison of the Accuracy of the Probabilistic Distance Clustering Method and Cluster Ensembles

2016 ◽  
Vol 3 (322) ◽  
Author(s):  
Dorota Rozmus
Keyword(s):  
Experimental Study ◽  
Clustering Algorithms ◽  
High Accuracy ◽  
Clustering Method ◽  
Cluster Ensembles ◽  
Clustering Problem ◽  
Probabilistic Distance ◽  
Accuracy Of Results

High accuracy of results is a very important aspect in any clustering problem t determines the effectiveness of decisions based on them. Therefore, literature proposes methods and solutions that aim to give more accurate and stable results than traditional clustering algorithms (e.g. k-means or hierarchical methods). Cluster ensembles (Leisch 1999; Dudoit, Fridlyand 2003; Hornik 2006; Fred, Jain 2002) or the distance clustering method (Ben-Israel, Iyigun 2008) are the examples of such solutions. Here, we carry out an experimental study to compare the accuracy of these two approaches.

scholarly journals The impact of semantic relations on grammatical alternation: an experimental study of proper name modifiers and determiner genitives

2019 ◽  
Vol 23 (4) ◽  
pp. 797-826 ◽  
Author(s):  
TINE BREBAN ◽  
JULIA KOLKMANN ◽  
JOHN PAYNE
Keyword(s):  
Experimental Study ◽  
Natural Language ◽  
Experimental Approach ◽  
Semantic Relations ◽  
Initial Finding ◽  
Proper Name ◽  
The Impact

In this article we investigate the role of semantic relations in grammatical alternations. The specific alternation we look at is that between the proper name modifier construction, e.g.the Obama government, and the determiner genitive, e.g.Obama's government. Through the use of an experimental study in which participants were asked to rate the naturalness of the two constructions in 20 attested natural language contexts and provide paraphrases of the semantic relations in question, we tested when the two constructions alternate and whether either construction expresses semantic relations that block alternation. Our initial finding is that none of the relations we studied is categorically associated with only one of the constructions, but that certain relations – notably possession and name – are far more preferentially associated with determiner genitives and proper name modifiers respectively. Despite these ‘default’ associations, participants nevertheless identified a range of possible interpretations for many of the examples, meaning that our study simultaneously supports the opposing theoretical views of default relations and semantic underspecification. Further, our study validates the inclusion of semantic relations in genitive alternation studies as a major factor despite the notorious difficulties in their operationalisation. Animacy distinctions, although more straightforward to codify, appear to be of lesser importance. Methodologically, our study shows the value of an experimental approach as a corrective to researcher intuitions about the identification of semantic relations in context.

Experimental Study on the Shaft Laser Cladding Bending and the Establishment of the Empirical Formula

2011 ◽  
Vol 120 ◽  
pp. 226-229
Author(s):  
Hui Zheng ◽  
Guo Dong Wang ◽  
Zhi Ren Han
Keyword(s):  
Experimental Study ◽  
Laser Beam ◽  
Laser Cladding ◽  
Empirical Formula ◽  
Mathematical Formulation ◽  
High Accuracy ◽  
Average Error ◽  
Direct Proportion ◽  
Shaft Length ◽  
Maximal Error

In order to study the influence of the layer of the laser cladding to the bending degree, obtain the mathematical formulation in shaft laser cladding bending and derive the empirical formula, the laser cladding test for shaft was designed. The laser cladding test had been proceeded at the same cladding area and different layer of cladding. The results of the experiment show that the shaft is bended facing the laser beam. The bending degree and the layer of laser cladding are at the direct proportion. At the same time mathematical formulation in shaft laser cladding bending has been established and the parameter which is used to measure the degree of the bending has been obtained. Empirical formula between bending degree and the layer of laser cladding has been established. The circular run-out formula along the shaft length has been derived. The calculated value and the measured value are of the goodness fit. The maximal error is 0.035mm, and the average error is 0.017mm. It illustrates that the mathematic formulation is correct and the empirical formula has high accuracy.

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