Mining compound words and their pronunciations is essential for Japanese input method editors (IMEs). We propose to use a chunk-based dependency parser to mine new words, collocations and predicate-argument phrases from largescale Japanese Web pages and tweets. The pronunciations of the compound words are automatically rewritten by a statistical machine translation (SMT) model. Experiments on a...

This paper presents a lexicon model for subjectivity description of Dutch verbs that offers a framework for the development of sentiment analysis and opinion mining applications based on a deep syntactic-semantic approach. The model aims to describe the detailed subjectivity relations that exist between the participants of the verbs, expressing multiple attitudes for each verb sense. Validation...

This paper presents the results of developing subjectivity classifiers for Implicit Opinion Question (IOQ) identification. IOQs are defined as opinion questions with no opinion words. An IOQ example is “will the U.S. government pay more attention to the Pacific Rim?” Our analysis on community questions of Yahoo! Answers shows that a large proportion of opinion questions are IOQs. It is thus imp...

Automatic Construction of a Contextual Valence Shifters Lexicon The research presented in this paper takes place in the field of Opinion Mining, which is mainly devoted to assigning a positive or negative label to a text or a sentence. The context of a highly polarized word plays an essential role, as it can modify its original polarity. The present work addresses this issue and focuses on the ...

In image annotation, the annotation words are expected to represent image content at both visual level and semantic level. However, a single word sometimes is ambiguous in annotation, for example, ”apple” may refer to a fruit or a company. However, when ”apple” combines with ”phone” or ”fruit”, it will be more semantically and visually consistent. In this paper, we attempt to find this kind of ...

We propose a method that processes raw informal medical texts (from health forums) and formal texts (outpatient records) in Bulgarian language in order to extract typical word co-occurrences in the form of association rules. When mining these rules we use some context information and small terminological lexicons to generalize the extracted frequent patterns. This allows to study informal expre...

Open-class semantic lexicon induction is of great interest for current knowledge harvesting algorithms. We propose a general framework that uses patterns in bootstrapping fashion to learn open-class semantic lexicons for different kinds of relations. These patterns require seeds. To estimate the goodness (the potential yield) of new seeds, we introduce a regression model that considers the conn...

Most opinion mining methods in English rely successfully on sentiment lexicons, such as English SentiWordnet (ESWN). While there have been efforts towards building Arabic sentiment lexicons, they suffer from many deficiencies: limited size, unclear usability plan given Arabic’s rich morphology, or nonavailability publicly. In this paper, we address all of these issues and produce the first publ...

This work reviews and elaborates a methodology for hierarchical multi-scale set-class analysis of music pieces. The method extends the systematic segmentation and representation of Sapp’s ‘keyscapes’ to the description stage, by introducing a set-class level of description. This provides a systematic, mid-level, and standard analytical lexicon, which allows the description of any notated music ...

The present research exploits the large amount of linguistic resources developed into the Lexicon-grammar paradigm in the domain of the Opinion Mining. Grounded on the Semantic Predicates theory, the proposed system is able to automatically match the syntactic structures selected by special classes of verbs, indicating positive or negative Sentiment, Opinion or Physical acts, with the semantic ...