• Varying annotated expressions so that cannot be acquired rules state descriptiontypes. Therefore it is necessary to gather automatically corpusand to extract features of description types.Some interesting leading studies have been conducted on discourse analysison the Japanese language [51, 95, 170, 175]. However, for actual answer corpusof question-answering in Japanese, previous work is merely found. Maynard [88]explored the structures of answers in Q&A of radio programs and tried to typifythem.4.2.3 Answering proceduresIn recent open domain question-answering, I have seen many studies that respondswith definitions, reasons, and reputations. However, there have beenonly a few leading researches on question-answering that responds with methods.Studies on method retrieval with limited text styles and domains such assearching for patents [32, 122] and cooking recipes [40, 121, 125] have been conductedfor a long time. Questions related to all procedures were addressed by anexpert system [9]. However, only a few studies have been conducted on questionansweringthat responds by searching for methods from an open domain text setsuch as Web texts [5, 135–137, 163]. Additionally, such kind of question-answeringsystem requires a more flexible and more machine-operable approach because ofthe diversity and changeable nature of the information resources. Recently, themost successful approach has been to combine many shallow clues in the textsand occasionally in other linguistic resources. In this approach, the performanceof passage retrieval and categorization is vital for the performance of the entiresystem. In particular, the productiveness of the knowledge of expressions correspondingto each question type, which is principally exploited in retrieval andcategorization, is important. In this sense, the requirements for categorizationin such applications are different from those in previous categorizations. In textcategorization research, feature selection has been discussed [120, 130, 132, 162].However, most of the research dealt with categorization into taxonomy relatedto domain and genre. The features that are used are primarily content words,such as nouns, verbs, and adjectives; functional words and frequent formative50
elements were usually eliminated. However, some particular areas of text categorization,for example, authorship identification, suggested the feasibility of textcategorization with functional expressions on a different axis of document topics[63, 147, 187].4.3 Annotating description types of answersAs stated at the beginning of this chapter, the classification of answers has oftenbeen discussed as it is integrated with the classification of questions. However,there are no established categories of descriptive answers, and the relationshipsbetween classification categories and question categories have not been clarifiedeither. Therefore, I conducted an experiment to classify answers using the classificationcategories based on the discursive features on general texts that wereproposed in leading studies. The classification was performed by tagging the answerarticles. I tried to clarify necessary conditions for categories of descriptiveanswers and those tagging methods.4.3.1 description typesTo further explore description types of answers, this thesis considered the frameworkto solve four problems comprising those described in last section. For thefirst problem of collection of corpus for annotating description type and the secondproblem of reduction of annotation cost for tagging, this thesis suppose a networkenvironment for anonymous annotators tagging descriptive types to articles.To realize such kind of annotation framework, at least, I have to know any descriptiontypes that can be stably assigned by non-professional annotators. Thisthesis supposed instructions of annotations and definitions of description types ina level of book of technical writing for general readers, and then investigated thefeasibility of annotation in such kind of discursive features of text. For the thirdproblems, this thesis stands on machine learning based approaches to automaticallyacquire rules to specify descriptive type from tagged corpus. Finally, forthe forth problem of feature analysis for answers in Japanese question-answering,I conducted annotation of description types to answers in a actual web Q&Aservice, and examine the features of description types.51
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