A collocation is a habitual word combination. Collocational knowledge is essential for many tasks in natural language processing. We present a method for extracting collocations from text corpora. By comparison with the SUSANNE corpus, we show that both high precision and broad coverage can be achieved with our method. Finally, we describe an application of the automatically extracted collocati...

The aim of this paper is to discuss aspects of an on-going project on the development of grammatical and lexical resources for Zulu with sufficient coverage for unrestricted text. We explain how the basic software tools of computational morphology are used in linguistic processing, more specifically for automatic word form recognition and morphological tagging of the growing stock of electronic...

A leading text for undergraduateand graduate-level courses, this book introduces widely used forms of remote sensing imagery and their applications in plant sciences, hydrology, earth sciences, and land use analysis. The text provides comprehensive coverage of principal topics and serves as a framework for organizing the vast amount of remote sensing information available on the Web. Featuring ...

Traditional models of parsing as used in interfaces have shown to be weak and ine ective in complex tasks such as processing of naturally-occurring texts. Broad coverage parsers go mad when confronted with extended inputs without su cient information to control the interpretation process. The use of e ective control strategies is necessary to overcome these shortcomings. Extra-linguistic criter...

Our purpose is to present a method to lexically evaluate the results of extracting in an unsupervised way material from text corpora to build ontologies. We have worked on a legal corpus (EU VAT directive) consisting of 43K words. The unsupervised text miner has produced a set of triples. These are to be used as preprocessed material for the construction of ontologies from scratch. A quantitati...

The Recognizing Textual Entailment System shown here is based on the use of a broad-coverage parser to extract dependency relationships; in addition, WordNet relations are used to recognize entailment at the lexical level. The work investigates whether the mapping of dependency trees from text and hypothesis give better evidence of entailment than the matching of plain text alone. While the use...

An experimental speech recognition system was developed for German using an already existing technology reported elsewhere (1). The system recognizes complete sentences when the words are spoken with a small pause in between. The user has to train the system in advance by uttering 110 short sentences. The size of the system's vocabulary is presently limited to about 1300 words, with a coverage ...

AI applications often receive their input in the form of natural language text, or as the transcription of spoken text. A commonsense inference system should transform such input to a formal representation with limited vocabulary in order to be able to process them. In this paper, we present a method based on neural word embeddings that automatically assigns semic features to words of natural l...

BACKGROUND Traditionally text mention normalization corpora have normalized concepts to single ontology identifiers ("pre-coordinated concepts"). Less frequently, normalization corpora have used concepts with multiple identifiers ("post-coordinated concepts") but the additional identifiers have been restricted to a defined set of relationships to the core concept. This approach limits the abili...

While genetic diversity can be quantified accurately from high coverage sequencing data, it is often desirable to obtain such estimates from data with low coverage, either to save costs or because of low DNA quality, as is observed for ancient samples. Here, we introduce a method to accurately infer heterozygosity probabilistically from sequences with average coverage [Formula: see text] of a s...