Articles

This paper proposes a new paradigm for senti- ment analysis: translation from text documents to a set of sentiment units. The techniques of deep language analysis for machine translation are applicable also to this kind of text mining task. We developed a high-precision sentiment analysis system at a low development …...

For Information Retrieval, users are more concerned about the precision of top ranking documents in most practical situations. In this paper, we propose a method to improve the precision of top N ranking documents by reordering the retrieved documents from the initial retrieval. To reorder documents, we first automatically extract …...

This paper investigates the use of concept- based representations for text categoriza- tion. We introduce a new approach to cre- ate concept-based text representations, and apply it to a standard text categorization collection. The representations are used as input to a Support Vector Machine classi- fier, and the results show …...

In this paper, the search engine Intuition is described. It allows the user to navigate through the documents retrieved with a given query. Several “browse help” functions are provided by the engine and described here: conceptualisation, named entities, similar documents and entity visualization. They intend to “save the user’s time”. …...

The work presented in this paper is the first step in a project which aims to cluster and sum- marise electronic discussions in the context of help-desk applications. The eventual objective of this project is to use these summaries to as- sist help-desk users and operators. In this pa- per, …...

In this paper, we present a hybrid method for Chinese and Japanese word segmentation. Word-level information is useful for analysis of known words, while character-level informa- tion is useful for analysis of unknown words, and the method utilizes both these two types of information in order to effectively handle known …...

We introduce a character-based chunking for un- known word identification in Japanese text. A major advantage of our method is an ability to detect low frequency unknown words of unrestricted character type patterns. The method is built upon SVM-based chunking, by use of character n-gram and surround- ing context of …...

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 introduce the “dependency tree path” (DTP). Next, we calcu- late the similarity between DTPs based on the ESK (Extended String …...

In this paper we present the dialogue- understanding components of an architec- ture for assisting multi-human conversa- tions in artifact-producing meetings: meet- ings in which tangible products such as project planning charts are created. Novel aspects of our system include multimodal ambiguity resolution, modular ontology- driven artifact manipulation, and a …...

Manually annotating the rhetorical struc- ture of texts is very labour-intensive. At the same time, high-quality automatic analysis is currently out of reach. We thus propose to split the manual annotation in two phases: the simpler marking of lexical connectives and their relations, and the more difficult decisions on overall …...

We explore unsupervised language model adaptation techniques for Statistical Machine Translation. The hypotheses from the machine translation output are converted into queries at different levels of representation power and used to extract similar sentences from very large monolingual text collection. Specific language models are then build from the retrieved data …...

Empirical experience and observations have shown us when powerful and highly tunable classifiers such as maximum en- tropy classifiers, boosting and SVMs are applied to language processing tasks, it is possible to achieve high accuracies, but eventually their performances all tend to plateau out at around the same point. To …...

Selecting important information while account- ing for repetitions is a hard task for both sum- marization and question answering. We pro- pose a formal model that represents a collec- tion of documents in a two-dimensional space of textual and conceptual units with an asso- ciated mapping between these two dimensions. …...

We describe a simple approach for integrating shallow and deep parsing. We use phrase struc- ture bracketing obtained from the Collins parser as filters to guide deep parsing. Our exper- iments demonstrate that our technique yields substantial gains in speed along with modest improvements in accuracy. 1...

Tree-based approaches to alignment model translation as a sequence of probabilistic op- erations transforming the syntactic parse tree of a sentence in one language into that of the other. The trees may be learned directly from parallel corpora (Wu, 1997), or provided by a parser trained on hand-annotated treebanks (Ya- …...

In this paper we illustrate and evaluate an approach to the creation of high quality linguistically annotated resources based on the exploitation of aligned parallel corpora. This approach is based on the assumption that if a text in one language has been annotated and its translation has not, annotations can …...

We investigate unsupervised techniques for acquiring monolingual sentence-level paraphrases from a corpus of temporally and topically clustered news articles collected from thousands of web-based news sources. Two techniques are employed: (1) simple string edit distance, and (2) a heuristic strategy that pairs initial (presumably summary) sentences from different news stories …...

This paper proposes unsupervised word sense disambiguation based on automati- cally constructed case frames and its in- corporation into our zero pronoun resolu- tion system. The word sense disambigua- tion is applied to verbs and nouns. We consider that case frames define verb senses and semantic features in a thesaurus …...

This paper presents a system for automati- cally generating discourse structures from written text. The system is divided into two levels: sentence-level and text-level. The sentence-level discourse parser uses syntactic information and cue phrases to segment sen- tences into elementary discourse units and to generate discourse structures of sentences. At …...

This paper addressees the problem of eliminat- ing unsatisfactory outputs from machine trans- lation (MT) systems. The authors intend to eliminate unsatisfactory MT outputs by using confidence measures. Confidence measures for MT outputs include the rank-sum-based confi- dence measure (RSCM) for statistical machine translation (SMT) systems. RSCM can be ap- …...