Latent Semantic Analysis

Contextual spelling errors are defined as the use of an incorrect, though valid, word in a particular sentence or context. Tra- ditional spelling checkers flag misspelled words, but they do …...

We seek a knowledge-free method for inducing multiword units from text corpora for use as machine-readable dictionary headwords. We provide two major evaluations of nine existing collocation-finders and illustrate the …...

We present a comparative evaluation of two data-driven models used in translation selec- tion of English-Korean machine translation. La- tent semantic analysis(LSA) and probabilistic latent semantic analysis (PLSA) are applied …...

This paper describes an unsupervised algo- rithm for placing unknown words into a taxon- omy and evaluates its accuracy on a large and varied sample of words. The algorithm works …...

In this paper we demonstrate methods of im- proving both the recall and the precision of au- tomatic methods for extraction of hyponymy (IS A) relations from free text. By …...

We discuss Feature Latent Semantic Analysis (FLSA), an extension to Latent Semantic Analysis (LSA). LSA is a statistical method that is ordinar- ily trained on words only; FLSA adds to …...

In this paper we describe the (annotation) tools underly- ing two automatic techniques to analyse the meaning and use of backward causal connectives in large Dutch newspaper corpora. With the …...

Statistical language models using n-gram approach have been under the criticism of neglecting large-span syntactic-semantic in- formation that influences the choice of the next word in a language. One of …...

The conventional n-gram language model exploits only the immediate context of historical words without exploring long-distance semantic information. In this paper, we present a new information source extracted from latent …...

Probabilistic Latent Semantic Analysis (PLSA) models have been shown to pro- vide a better model for capturing poly- semy and synonymy than Latent Seman- tic Analysis (LSA). However, the param- …...

AbstractTranslation adequacy is defined as the amount of semantic content from the source language document that is conveyed in the target language document. As such, it is more difficult to …...

This paper summarizes FBK-irst participa- tion at the lexical substitution task of the SEMEVAL competition. We submitted two different systems, both exploiting synonym lists extracted from dictionaries. For each word …...

Most current word prediction systems make use of n-gram language models (LM) to es- timate the probability of the following word in a phrase. In the past years there have …...

In this paper, we describe our two SemEval- 2007 entries. Our first entry, for Task 5: Multilingual Chinese-English Lexical Sam- ple Task, is a supervised system that decides the most …...

Latent Semantic Analysis (LSA) is based on the Singular Value Decompo- sition (SVD) of a term-by-document matrix for identifying relationships among terms and documents from co- occurrence patterns. Among the …...

We describe an entirely statistics-based, unsupervised, and language- independent approach to multilingual information retrieval, which we call La- tent Morpho-Semantic Analysis (LMSA). LMSA overcomes some of the shortcomings of related …...

Good hypertext writing style mandates that link texts clearly indicate the nature of the link tar- get. While this guideline is routinely ignored in HTML, the lightweight markup languages used …...

Though data-driven in nature, emotion analy- sis based on latent semantic analysis still relies on some measure of expert knowledge in or- der to isolate the emotional keywords or key- …...

. This study assesses the influence of semantic space on the acquisition of verbal lexicon. The studied one hundred and fifty action verbs extracted from the experimental data in M3 …...

We explore the near-synonym lexical choice problem using a novel representa- tion of near-synonyms and their contexts in the latent semantic space. In contrast to traditional latent semantic analysis (LSA), …...

AbstractIt is recognized that many evaluation metrics of machine translation in use that focus on surface word level suffer from their lack of tolerance of linguistic variance, and the incorporation …...

Text summarization solves the problem of extracting important information from huge amount of text data. There are vari- ous methods in the literature that aim to find out well-formed summaries. …...

The N400 is a human neuroelectric response to semantic incongruity in on-line sentence processing, and implausibility in context has been identified as one of the factors that influ- ence the …...

AbstractWe present several experiments aiming at measuring the semantic compositionality of NV expressions in Basque. Our approach is based on the hypothesis that compositionality can be related to distributional similarity. …...

Topic models are increasingly being used for text analysis tasks, often times replacing ear- lier semantic techniques such as latent seman- tic analysis. In this paper, we develop a novel …...

Existing vector space models typically map synonyms and antonyms to similar word vec- tors, and thus fail to represent antonymy. We introduce a new vector space representation where antonyms lie …...

The Semantic Textual Similarity (STS) shared task (Agirre et al., 2012) computes the degree of semantic equivalence between two sen- tences.1 We show that a simple unsupervised latent semantics based …...

Relation Extraction (RE) is the task of extracting semantic relationships between entities in text. Recent studies on rela- tion extraction are mostly supervised. The clear drawback of supervised methods is …...

AbstractMany Japanese words are made of kanji characters, which themselves represent meanings. However traditional word-based distributional semantic models (DSMs) do not benefit from the useful semantic information of kanji characters. …...

Accessing the web has been an efficient and effective means to acquire self-help knowledge when suf- fering from depressive problems. Many mental health websites have developed community-based ser- vices such …...

AbstractThis paper introduces a collection of freely available Latent Semantic Analysis models built on the entire English Wikipedia and the TASA corpus. The models differ not only on their source, …...

This paper provides system description of the cross-level semantic similarity task for the SEMEVAL-2014 workshop. Cross- level semantic similarity measures the de- gree of relatedness between texts of vary- ing …...

In this paper we present our contribution to SemEval-2014 Task 4: Aspect Based Sen- timent Analysis (Pontiki et al., 2014), Sub- task 2: Aspect Term Polarity for Laptop domain. The …...

Building comprehensive language models us- ing latent semantic analysis (LSA) requires substantial processing power. At the ideal pa- rameters suggested in the literature (for an overview, see Bradford, 2008) it …...

AbstractAbstract Meaning Representation (AMR) parsing aims at abstracting away from the syntactic realization of a sentence, and denote only its meaning in a canonical form. As such, it is ideal …...