Taking into account semantic similarities in correspondence analysis

Term-document matrices feed most distributional approaches to quantitative textual studies, without consideration for the semantic similarities between terms, whose presence arguably reduce the content variety. This contribution presents a formalism remedying this omission, and makes an explicit use of the semantic similarities as extracted from WordNet. A case study in similarity-reduced correspondence analysis illustrates the proposal

Verb similarity: comparing corpus and psycholinguistic data

Similarity, which plays a key role in fields like cognitive science, psycholinguistics and natural language processing, is a broad and multifaceted concept. In this work we analyse how two approaches that belong to different perspectives, the corpus view and the psycholinguistic view, articulate similarity between verb senses in Spanish. Specifically, we compare the similarity between verb senses based on their argument structure, which is captured through semantic roles, with their similarity defined by word associations. We address the question of whether verb argument structure, which reflects the expression of the events, and word associations, which are related to the speakers' organization of the mental lexicon, shape similarity between verbs in a congruent manner, a topic which has not been explored previously. While we find significant correlations between verb sense similarities obtained from these two approaches, our findings also highlight some discrepancies between them and the importance of the degree of abstraction of the corpus annotation and psycholinguistic representations.La similitud, que desempeña un papel clave en campos como la ciencia cognitiva, la psicolingüística y el procesamiento del lenguaje natural, es un concepto amplio y multifacético. En este trabajo analizamos cómo dos enfoques que pertenecen a diferentes perspectivas, la visión del corpus y la visión psicolingüística, articulan la semejanza entre los sentidos verbales en español. Específicamente, comparamos la similitud entre los sentidos verbales basados en su estructura argumental, que se capta a través de roles semánticos, con su similitud definida por las asociaciones de palabras. Abordamos la cuestión de si la estructura del argumento verbal, que refleja la expresión de los acontecimientos, y las asociaciones de palabras, que están relacionadas con la organización de los hablantes del léxico mental, forman similitud entre los verbos de una manera congruente, un tema que no ha sido explorado previamente. Mientras que encontramos correlaciones significativas entre las similitudes de los sentidos verbales obtenidas de estos dos enfoques, nuestros hallazgos también resaltan algunas discrepancias entre ellos y la importancia del grado de abstracción de la anotación del corpus y las representaciones psicolingüísticas.La similitud, que exerceix un paper clau en camps com la ciència cognitiva, la psicolingüística i el processament del llenguatge natural, és un concepte ampli i multifacètic. En aquest treball analitzem com dos enfocaments que pertanyen a diferents perspectives, la visió del corpus i la visió psicolingüística, articulen la semblança entre els sentits verbals en espanyol. Específicament, comparem la similitud entre els sentits verbals basats en la seva estructura argumental, que es capta a través de rols semàntics, amb la seva similitud definida per les associacions de paraules. Abordem la qüestió de si l'estructura de l'argument verbal, que reflecteix l'expressió dels esdeveniments, i les associacions de paraules, que estan relacionades amb l'organització dels parlants del lèxic mental, formen similitud entre els verbs d'una manera congruent, un tema que no ha estat explorat prèviament. Mentre que trobem correlacions significatives entre les similituds dels sentits verbals obtingudes d'aquests dos enfocaments, les nostres troballes també ressalten algunes discrepàncies entre ells i la importància del grau d'abstracció de l'anotació del corpus i les representacions psicolingüístiques

On the cross-linguistic equivalence of sentir(e) in Romance languages: a contrastive study in semantics

Recent linguistic studies on perception have focused mainly on verbs referring to the dominant visual and auditory modalities, (e.g. English see/look and hear/listen) and have largely ignored the minor verbs. The present paper seeks to fill this gap by comparing the complex semantics of the cognate verbs sentir(e) in three Romance languages, namely Spanish, French and Italian. Because the objective study of semantics is a problematic issue, we pay special attention to methodological problems and opt for a combined corpus approach involving both a translation corpus and comparable data. Evidence from both corpora indicates that, notwithstanding the fact that the rich polysemy of the three verbs partly coincides, each individual verb has undergone semantic specializations differentiating the morphological cognates

Detecting Policy Preferences and Dynamics in the UN General Debate with Neural Word Embeddings

Foreign policy analysis has been struggling to find ways to measure policy preferences and paradigm shifts in international political systems. This paper presents a novel, potential solution to this challenge, through the application of a neural word embedding (Word2vec) model on a dataset featuring speeches by heads of state or government in the United Nations General Debate. The paper provides three key contributions based on the output of the Word2vec model. First, it presents a set of policy attention indices, synthesizing the semantic proximity of political speeches to specific policy themes. Second, it introduces country-specific semantic centrality indices, based on topological analyses of countries' semantic positions with respect to each other. Third, it tests the hypothesis that there exists a statistical relation between the semantic content of political speeches and UN voting behavior, falsifying it and suggesting that political speeches contain information of different nature then the one behind voting outcomes. The paper concludes with a discussion of the practical use of its results and consequences for foreign policy analysis, public accountability, and transparency

An information retrieval approach to ontology mapping

In this paper, we present a heuristic mapping method and a prototype mapping system that support the process of semi-automatic ontology mapping for the purpose of improving semantic interoperability in heterogeneous systems. The approach is based on the idea of semantic enrichment, i.e., using instance information of the ontology to enrich the original ontology and calculate similarities between concepts in two ontologies. The functional settings for the mapping system are discussed and the evaluation of the prototype implementation of the approach is reported. \ud \u

Statistical analysis of the owl:sameAs network for aligning concepts in the linking open data cloud

The massively distributed publication of linked data has brought to the attention of scientific community the limitations of classic methods for achieving data integration and the opportunities of pushing the boundaries of the field by experimenting this collective enterprise that is the linking open data cloud. While reusing existing ontologies is the choice of preference, the exploitation of ontology alignments still is a required step for easing the burden of integrating heterogeneous data sets. Alignments, even between the most used vocabularies, is still poorly supported in systems nowadays whereas links between instances are the most widely used means for bridging the gap between different data sets. We provide in this paper an account of our statistical and qualitative analysis of the network of instance level equivalences in the Linking Open Data Cloud (i.e. the sameAs network) in order to automatically compute alignments at the conceptual level. Moreover, we explore the effect of ontological information when adopting classical Jaccard methods to the ontology alignment task. Automating such task will allow in fact to achieve a clearer conceptual description of the data at the cloud level, while improving the level of integration between datasets. <br/

A Progressive Clustering Algorithm to Group the XML Data by Structural and Semantic Similarity

Since the emergence in the popularity of XML for data representation and exchange over the Web, the distribution of XML documents has rapidly increased. It has become a challenge for researchers to turn these documents into a more useful information utility. In this paper, we introduce a novel clustering algorithm PCXSS that keeps the heterogeneous XML documents into various groups according to their similar structural and semantic representations. We develop a global criterion function CPSim that progressively measures the similarity between a XML document and existing clusters, ignoring the need to compute the similarity between two individual documents. The experimental analysis shows the method to be fast and accurate