Proceedings of the Morpho Challenge 2010 Workshop

In natural language processing many practical tasks, such as speech recognition, information retrieval and machine translation depend on a large vocabulary and statistical language models. For morphologically rich languages, such as Finnish and Turkish, the construction of a vocabulary and language models that have a sufficient coverage is particularly difficult, because of the huge amount of different word forms. In Morpho Challenge 2010 unsupervised and semi-supervised algorithms are suggested to provide morpheme analyses for words in different languages and evaluated in various practical applications. As a research theme, unsupervised morphological analysis has received wide attention in conferences and scientific journals focused on computational linguistic and its applications. This is the proceedings of the Morpho Challenge 2010 Workshop that contains one introduction article with a description of the tasks, evaluation and results and six articles describing the participating unsupervised and supervised learning algorithms. The Morpho Challenge 2010 Workshop was held at Espoo, Finland in 2-3 September, 2010.reviewe

A Task-based Evaluation of French Morphological Resources and Tools

Morphology is a key component for many Language Technology applications. However, morphological relations, especially those relying on the derivation and compounding processes, are often addressed in a superficial manner. In this article, we focus on assessing the relevance of deep and motivated morphological knowledge in Natural Language Processing applications. We first describe an annotation experiment whose goal is to evaluate the role of morphology for one task, namely Question Answering (QA). We then highlight the kind of linguistic knowledge that is necessary for this particular task and propose a qualitative analysis of morphological phenomena in order to identify the morphological processes that are most relevant. Based on this study, we perform an intrinsic evaluation of existing tools and resources for French morphology, in order to quantify their coverage. Our conclusions provide helpful insights for using and building appropriate morphological resources and tools that could have a significant impact on the application performance

Enriching Morphological Lexica through Unsupervised Derivational Rule Acquisition

WoLeR 2011 is endorsed by FlaReNet, and supported by the Alpage team and the EDyLex French national grant (ANR-09-CORD-008).International audienceIn a morphological lexicon, each entry combines a lemma with a specific inflection class, often defined by a set of inflection rules. Therefore, such lexica usually give a satisfying account of inflectional operations. Derivational information, however, is usually badly covered. In this paper we introduce a novel approach for enriching morphological lexica with derivational links between entries and with new entries derived from existing ones and attested in large-scale corpora, without relying on prior knowledge of possible derivational processes. To achieve this goal, we adapt the unsupervised morphological rule acquisition tool MorphAcq (Nicolas et al., 2010) in a way allowing it to take into account an existing morphological lexicon developed in the Alexina framework (Sagot, 2010), such as the Lefff for French and the Leffe for Spanish. We apply this tool on large corpora, thus uncovering morphological rules that model derivational operations in these two lexica. We use these rules for generating derivation links between existing entries, as well as for deriving new entries from existing ones and adding those which are best attested in a large corpus. In addition to lexicon development and NLP applications that benefit from rich lexical data, such derivational information will be particularly valuable to linguists who rely on vast amounts of data to describe and analyse these specific morphological phenomena

Open-source resources and standards for Arabic word structure analysis: Fine grained morphological analysis of Arabic text corpora

Morphological analyzers are preprocessors for text analysis. Many Text Analytics applications need them to perform their tasks. The aim of this thesis is to develop standards, tools and resources that widen the scope of Arabic word structure analysis - particularly morphological analysis, to process Arabic text corpora of different domains, formats and genres, of both vowelized and non-vowelized text. We want to morphologically tag our Arabic Corpus, but evaluation of existing morphological analyzers has highlighted shortcomings and shown that more research is required. Tag-assignment is significantly more complex for Arabic than for many languages. The morphological analyzer should add the appropriate linguistic information to each part or morpheme of the word (proclitic, prefix, stem, suffix and enclitic); in effect, instead of a tag for a word, we need a subtag for each part. Very fine-grained distinctions may cause problems for automatic morphosyntactic analysis – particularly probabilistic taggers which require training data, if some words can change grammatical tag depending on function and context; on the other hand, finegrained distinctions may actually help to disambiguate other words in the local context. The SALMA – Tagger is a fine grained morphological analyzer which is mainly depends on linguistic information extracted from traditional Arabic grammar books and prior knowledge broad-coverage lexical resources; the SALMA – ABCLexicon. More fine-grained tag sets may be more appropriate for some tasks. The SALMA –Tag Set is a theory standard for encoding, which captures long-established traditional fine-grained morphological features of Arabic, in a notation format intended to be compact yet transparent. The SALMA – Tagger has been used to lemmatize the 176-million words Arabic Internet Corpus. It has been proposed as a language-engineering toolkit for Arabic lexicography and for phonetically annotating the Qur’an by syllable and primary stress information, as well as, fine-grained morphological tagging

First International Workshop on Lexical Resources

International audienceLexical resources are one of the main sources of linguistic information for research and applications in Natural Language Processing and related fields. In recent years advances have been achieved in both symbolic aspects of lexical resource development (lexical formalisms, rule-based tools) and statistical techniques for the acquisition and enrichment of lexical resources, both monolingual and multilingual. The latter have allowed for faster development of large-scale morphological, syntactic and/or semantic resources, for widely-used as well as resource-scarce languages. Moreover, the notion of dynamic lexicon is used increasingly for taking into account the fact that the lexicon undergoes a permanent evolution.This workshop aims at sketching a large picture of the state of the art in the domain of lexical resource modeling and development. It is also dedicated to research on the application of lexical resources for improving corpus-based studies and language processing tools, both in NLP and in other language-related fields, such as linguistics, translation studies, and didactics

Micro wholesaling businesses involved in the sector of confectionary products - strategies of survival and growth

It can be argued that the problematic situation where micro Greek wholesaling businesses find themselves has been a result of the strong presence of supermarkets and superstores in the last years. The researcher attempts to picture the current market reality that constitutes the background of the Thesis by posing the main research question: "How can micro Greek wholesaling businesses involved in the confectionary products' sector identify and implement suitable survival and growth strategies in order to cope with increasing competition in a market characterized by a large expansion of supermarkets and chain stores?". The factors that triggered research are related to the researcher's avocation with the sector of confectionary products; having worked in a micro family wholesaling enterprise in the past (and still involved in it occasionally when demand for confectionary products is increased), the survival and growth prospects of this firm constitutes an issue of high importance for the researcher and his family. The researcher believes that the study of similar wholesaling firms-case studies would highlight potential survival and growth strategies, useful for the family business; in this way, he holds the view that he contributes to the solution of an intense family problem. Apart from the personal interest for the survival and growth of micro wholesaling firms, it can be argued that the confectionary products' sector is a dynamic field that provides the opportunities to a researcher to evolve to a consultant or a specialist practitioner