Fashion recommendation systems are highly desired by customers to find visually-collocated fashion items, such as clothes, shoes, bags, etc. While existing methods demonstrate promising results, they remain lacking in flexibility and diversity, e.g. assuming a fixed number of items or favoring safe but boring recommendations. In this paper, we propose novel collocation framework, <bold xmlns:mm...

Aiming at the situation of current Chinese language resources shortage ,this paper proposes semantically selectional preferences of unsupervised learning method, and presents a strategy of obtaining verbnoun semantic collocation in Chinese. An approach of Chinese semantic preference learning, which is based on Latent Semantic Clustering model and Expectation Maximization Algorithm. First, the p...

Bootstrapping semantics from text is one of the greatest challenges in natural language learning. Earlier research showed that it is possible to automatically identify words that are semantically similar to a given word based on the syntactic collocation patterns of the words. We present an approach that goes a step further by obtaining a tree structure among the most similar words so that diie...

This paper proposes a novel method of learning probabilistic subcategorization preference. In the method, for the purpose of coping with the ambiguities of case dependencies and noun class generalization of argument/adjunct nouns, we introduce a data structure which represents a tuple of independent partial subcategorization frames. Each collocation of a verb and argument/adjunct nouns is assum...

This paper demonstrates a method for creating Japanese learners dictionary of i-adjective-noun collocations. After an introduction of the importance of collocations and the necessity of their inclusion in Japanese language learning, we present various corpora types and corpus query tools that are used to obtain variety of collocational usage in different types of discourse. The Japanese languag...

This study addresses issues of Japanese language learning concerning word combinations (collocations). Japanese learners may be able to construct grammatically correct sentences, however, these may sound “unnatural”. In this work, we analyze correct word combinations using different collocation measures and word similarity methods. While other methods use well-formed text, our approach makes us...

'l?his paper 1)rovidcs an at)l)roa(:h to tim semi-aul;onmtic exl;i'action of (:ollocaIJons f lom eorl)ora using sl;atisti(:s. The growing availability of lm'ge textual cort)ora, and the in(:reasing number of applications of colloeal;ion extra(:tion, has given risc~ 1;o wu.ious apt)roaches on the I;opi(:. In l;his palter, we address the probl(;m of 'ne,stcd collocrd, ions; thai, is, those being ...

This paper proposes a novel method of learning probabilistic subcategorization preference. In the method, for the purpose of coping with the ambiguities of case dependencies and noun class generalization of argument/adjunct nouns, we introduce a data structure which represents a tuple of independent partial subcategorization frames. Each collocation of a verb and argument/adjunct nouns is assum...

a back propagation artificial neural network (bpann) is a well-known learning algorithmpredicated on a gradient descent method that minimizes the square error involving the networkoutput and the goal of output values. in this study, 261 gps/leveling and 8869 gravity intensityvalues of iran were selected, then the geoid with three methods “ellipsoidal stokes integral”,“bpann”, and “collocation” ...

In this paper, we present a series of semantic analyses of words in political blogs in the setting of categorization of two opposite political orientations: liberal vs. conservative. We classify nouns, verbs, adjectives and adverbs into semantic categories by using the General Inquirer dictionary. Then distributions of these categories and correlations among them are examined both within and be...