Экспериментальные результаты

The paper reports on a new approach to automatic generation of back-of-book indexes for Chinese books. Parsing on the level of complete sentential analysis is avoided because of the inefficiency …...

Large-scale natural language generation re- quires the integration of vast mounts of knowledge: lexical, grammatical, and concep- tual. A robust generator must be able to operate well even when pieces …...

In this paper we deal with several kinds of anaphora in unrestricted texts. These kinds of anaphora are pronominal references, surface- count anaphora and one-anaphora. In order to solve these …...

AbstractIn this paper we describe and experimentally evaluate FromTo K/E, a rule-based Korean-English machine translation system adapting transfer methodology. In accordance with the view that a successful Korean-English machine translation …...

In our information era, keywords are very useful to information retrieval, text clustering and so on. News is always a domain attracting a large amount of attention. Aiming at news …...

This paper describes a novel framework for interactive question-answering (Q/A) based on predictive questioning. Gen- erated off-line from topic representations of complex scenarios, predictive ques- tions represent requests for information …...

In this paper, we propose a three-step multilingual dependency parser, which generalizes an efficient parsing algorithm at first phase, a root parser and post- processor at the second and third …...

We present a new approach to relation ex- traction that requires only a handful of train- ing examples. Given a few pairs of named entities known to exhibit or not …...

Traditionally, statistical machine translation systems have relied on parallel bi-lingual data to train a translation model. While bi-lingual parallel data are expensive to generate, mono- lingual data are relatively common. …...

A semantic parser learning system learns to map natural language sentences into their domain-specific formal meaning rep- resentations, but if the constructs of the meaning representation language do not correspond …...

This paper studies sentiment analysis of condi- tional sentences. The aim is to determine whether opinions expressed on different topics in a conditional sentence are positive, negative or neutral. Conditional …...

We propose a novel way of incorporating de- pendency parse and word co-occurrence in- formation into a state-of-the-art web-scale n- gram model for spelling correction. The syn- tactic and distributional …...

This paper proposes a method to improve shift-reduce constituency parsing by using lexical de- pendencies. The lexical dependency information is obtained from a large amount of auto-parsed data that is …...

This paper introduces a new approach to solve the Chinese Pinyin-to-character (PTC) con- version problem. The conversion from Chi- nese Pinyin to Chinese character can be re- garded as a …...

Concept-to-text generation refers to the task of automatically producing textual output from non-linguistic input. We present a joint model that captures content selection (“what to say”) and surface realization (“how …...

“Grounded” language learning employs train- ing data in the form of sentences paired with relevant but ambiguous perceptual contexts. B¨orschinger et al. (2011) introduced an ap- proach to grounded language …...

This paper studies the problem of identifying users who use multiple userids to post in so- cial media. Since multiple userids may belong to the same author, it is hard …...

Building characters for dialogue agents is im- portant in making the agents more friendly and human-like. To build such characters, utterances suitable for the designated charac- ters are usually manually …...

AbstractIn this study, we describe the use of back-channelling patterns extracted from a dialogue corpus as a mean to characterising text-based dialogue systems. Our goal was to provide system users …...

This paper presents a two-step procedure to extract positive meaning from verbal negation. We first generate potential positive interpre- tations manipulating syntactic dependencies. Then, we score them according to their …...

AbstractWith the explosive growth of Internet, more and more domain-specific environments appear, such as forums, blogs, MOOCs and etc. Domain-specific words appear in these areas and always play a critical …...

AbstractUser-generated content such as the questions on community question answering (CQA) forums does not always come with appropriate headlines, in contrast to the news articles used in various headline generation …...

AbstractCode-mixing, the interleaving of two or more languages within a sentence or discourse is ubiquitous in multilingual societies. The lack of code-mixed training data is one of the major concerns …...

AbstractGenerating a vivid, novel, and diverse essay with only several given topic words is a promising task of natural language generation. Previous work in this task exists two challenging problems: …...

AbstractDisease is one of the fundamental entities in biomedical research. Recognizing such entities from biomedical text and then normalizing them to a standardized disease vocabulary offer a tremendous opportunity for …...

AbstractA mind-map is a diagram that represents the central concept and key ideas in a hierarchical way. Converting plain text into a mind-map will reveal its key semantic structure and …...

In this paper, we propose a novel self- supervised opinion summarization framework TransSum, which models opinion sum- maries as translations operating on the low-dimensional aspect and sentiment em- bedding spaces. …...

AbstractFunctional Distributional Semantics is a linguistically motivated framework for modelling lexical and sentence-level semantics with truth-conditional functions using distributional information. Previous implementations of the framework focus on subjectverbobject (SVO) triples …...

AbstractSexism is a growing online problem. It harms women who are targeted and makes online spaces inaccessible and unwelcoming. In this paper, we present our approach for Task A of …...