Ұқсастық Өлшемі

Our work focuses on identifying various types of lexical data in large corpora through statistical analysis. In this paper, we present a method for grouping adjectives according to their mean- …...

This paper describes a method for finding struc- rural matching between parallel sentences of two languages, (such as Japanese and English). Par- allel sentences are analyzed based on unification grammars, …...

In this paper we present a method to group adjectives according to their meaning, as a first step towards the automatic identification of adjectival scales. We discuss the properties of …...

This paper . proposes a similarity measure which takes account of point- of-views (abbreviated to POV, hereafter) in the calculation of similarity values. So far many researches on similarity measures …...

We describe an approach to tagging a monolin- gual dictionary with linguistic features. In par- ticular, we annotate the dictionary entries with parts of speech, number, and tense information. The …...

This work investigates the variation in a word’s dis- tributionally nearest neighbours with respect to the similarity measure used. We identify one type of variation as being the relative frequency …...

In this paper, we describe a method of automatic sentence alignment for building extracts from ab- stracts in automatic summarization research. Our method is based on two steps. First, we …...

This paper describes the exemplar based ap- proach presented by UNED at Senseval-3. In- stead of representing contexts as bags of terms and defining a similarity measure between con- texts, …...

We address the rating-inference problem, wherein rather than simply decide whether a review is “thumbs up” or “thumbs down”, as in previous sentiment analy- sis work, one must determine an …...

In this paper we define a novel similarity measure between examples of textual en- tailments and we use it as a kernel func- tion in Support Vector Machines (SVMs). This …...

This paper presents a novel approach to the semi-supervised learning of Informa- tion Extraction patterns. The method makes use of more complex patterns than previous approaches and determines their similarity …...

This paper explores the problem of com- puting text similarity between verb phrases describing skilled human behav- ior for the purpose of finding approximate matches. Four parsers are evaluated on …...

AbstractThis paper proposes the method to detect peculiar examples of the target word from a corpus. In this paper we regard following examples as peculiar examples: (1) a meaning of …...

We re-investigate the rationale for and the ef- fectiveness of adopting the notions of depth and density in WordNet-based semantic sim- ilarity measures. We show that the intuition for including …...

AbstractWikipedia articles in different languages have been mined to support various tasks, such as Cross-Language Information Retrieval (CLIR) and Statistical Machine Translation (SMT). Articles on the same topic in different …...

Recommendation systems (RS) take advan- tage of products and users information in order to propose items to consumers. Collaborative, content-based and a few hybrid RS have been developed in the …...

Lexical resource alignment has been an active field of research over the last decade. However, prior methods for align- ing lexical resources have been either spe- cific to a particular …...

AbstractPortuguese is a less resourced language in what concerns foreign language learning. Aiming to inform a module of a system designed to support scientific written production of Spanish native speakers …...

This paper presents an approach to simulate automatic speech recognition (ASR) errors from manual transcriptions and describes how it can be used to improve the performance of spoken language understanding …...

AbstractThe most important obstacles facing multi-document summarization include excessive redundancy in source descriptions and the looming shortage of training data. These obstacles prevent encoder-decoder models from being used directly, but …...

AbstractArabic dialects are the non-standard varieties of Arabic commonly spoken – and increasingly written on social media – across the Arab world. Arabic dialects do not have standard orthographies, a …...

AbstractWord embedding-based similarity measures are currently among the top-performing methods on unsupervised semantic textual similarity (STS) tasks. Recent work has increasingly adopted a statistical view on these embeddings, with some …...

AbstractMulti-task learning (MTL) and transfer learning (TL) are techniques to overcome the issue of data scarcity when training state-of-the-art neural networks. However, finding beneficial auxiliary datasets for MTL or TL …...