Existing graph-based ranking methods for keyphrase extraction compute a single importance score for each word via a single random walk. Motivated by the fact that both documents and words can be represented by a mixture of semantic topics, we propose to decompose traditional random walk into multiple random walks specific to various topics. We thus build a Topical PageRank (TPR) on word graph t...

Transforming Selected Concepts Into Dimensions in Latent Semantic Analysis Ricardo Olmos, Guillermo Jorge-Botana, José Antonio León & Inmaculada Escudero a Departamento de Psicologia Social y Metodologia, Universidad Autónoma de Madrid, Madrid, Spain b Departamento de Psicologia Evolutiva, Universidad Nacional de Educación a Distancia, Madrid, Spain c Departamento de Psicologia Basica, Universi...

E-assessment is an important component of e-learning and e-qualification. Formative and summative assessment serve different purposes and both types of evaluation are critical to the pedagogical process. While students are studying, practicing, working, or revising, formative assessment provides direction, focus, and guidance. Summative assessment provides the means to evaluate a learner’s achi...

Modeling text document similarity is an important yet challenging task. Even the most advanced computational linguistic models often misjudge document similarity relative to humans. Regarding the pattern of misjudgment between models and humans, Lee and colleagues (2005) suggested that the models’ primary failure is occasional underestimation of strong similarity between documents. According to...

This paper presents a new statistical method for detecting and tracking changes in word meaning, based on Latent Semantic Analysis. By comparing the density of semantic vector clusters this method allows researchers to make statistical inferences on questions such as whether the meaning of a word changed across time or if a phonetic cluster is associated with a specific meaning. Possible applic...

Certain previous researches attempted to characterize how association memory works. The word meanings derived from LSA (latent semantic analysis) are usually showed highly related to the performance of forward association memory. A naı̈ve postulation would assume that the mechanisms for that relationship are mainly due to the processes of semantic similarity. The present work not only validates ...

This paper presents a constructioninspecific model of multiword expression decomposability based on latent semantic analysis. We use latent semantic analysis to determine the similarity between a multiword expression and its constituent words, and claim that higher similarities indicate greater decomposability. We test the model over English noun-noun compounds and verb-particles, and evaluate ...

Résumé. L’analyse sémantique latente (LSA Latent Semantic Analysis) est aujourd’hui utilisée dans de nombreux domaines comme la modélisation cognitive, les applications éducatives mais aussi pour la classification. L’approche présentée dans cet article consiste à ajouter des informations grammaticales à LSA. Différentes méthodes pour exploiter ces informations grammaticales sont étudiées dans l...

The alignment of bargaining positions is crucial to a successful negotiation. Prior research has shown that similarity in language use is indicative of the conceptual alignment of interlocutors. We use latent semantic analysis to explore how the similarity of language use between negotiating parties develops over the course of a three-party negotiation. Results show that parties that reach an a...

English. The hypothesis that grammatical class information is represented in the mental lexicon and that it is activated during lexical access has generated a wide literature about the differences between nouns and verbs. However, the available evidences are dis-