A “sentence pattern” in modern Natural Language Processing is often considered as a subsequent string of words (n-grams). However, in many branches of linguistics, like Pragmatics or Corpus Linguistics, it has been noticed that simple n-gram patterns are not sufficient to reveal the whole sophistication of grammar patterns. We present a language independent architecture for extracting from sentences more sophisticated patterns than n-grams. In this architecture a “sentence pattern” is considered as n-element ordered combination of sentence elements. Experiments showed that the method extracts significantly more frequent patterns than the usual n-gram approach
In this paper, we show the commonalities between aggregation processes in Natural Language Generatio...
Article dans revue scientifique avec comité de lecture.In natural language and especially in spontan...
This paper considers the issue of frequency consolidation in lists of different length word n-grams ...
A “sentence pattern ” in modern Natural Language Processing is often considered as a subsequent stri...
In this paper we discuss sentence generation strategy for pattern-based machine translation and thei...
Natural language sentence can be represented by means of graphs, where words, groups of pixels or va...
AbstractThis paper presents our research in detection of emotive (emotionally loaded) sentences. The...
International audienceIn this paper, we present a method based on data mining techniques to automati...
We address the problem of predicting a word from previous words in a sample of text. In particular, ...
The connection between language processing and combinatorics on words is natural. Historically, ling...
We propose a method for analyzing long complex and compound sentences that utilizes global struc-tur...
Language surface structures demonstrate regularities that make it possible to learn a capacity for p...
Verwimp L., Pelemans J., Van hamme H., Wambacq P., ''Extending n-gram language models based on equiv...
The string regeneration problem is the problem of generating a fluent sentence from a bag of words. ...
The goal of this research is to explore sentence structures expressed by parts of speech. Due to a s...
In this paper, we show the commonalities between aggregation processes in Natural Language Generatio...
Article dans revue scientifique avec comité de lecture.In natural language and especially in spontan...
This paper considers the issue of frequency consolidation in lists of different length word n-grams ...
A “sentence pattern ” in modern Natural Language Processing is often considered as a subsequent stri...
In this paper we discuss sentence generation strategy for pattern-based machine translation and thei...
Natural language sentence can be represented by means of graphs, where words, groups of pixels or va...
AbstractThis paper presents our research in detection of emotive (emotionally loaded) sentences. The...
International audienceIn this paper, we present a method based on data mining techniques to automati...
We address the problem of predicting a word from previous words in a sample of text. In particular, ...
The connection between language processing and combinatorics on words is natural. Historically, ling...
We propose a method for analyzing long complex and compound sentences that utilizes global struc-tur...
Language surface structures demonstrate regularities that make it possible to learn a capacity for p...
Verwimp L., Pelemans J., Van hamme H., Wambacq P., ''Extending n-gram language models based on equiv...
The string regeneration problem is the problem of generating a fluent sentence from a bag of words. ...
The goal of this research is to explore sentence structures expressed by parts of speech. Due to a s...
In this paper, we show the commonalities between aggregation processes in Natural Language Generatio...
Article dans revue scientifique avec comité de lecture.In natural language and especially in spontan...
This paper considers the issue of frequency consolidation in lists of different length word n-grams ...