LOOSE TERM-CENTRIC REPRESENTATION FOR TERM CLASSIFICATION IN ASPECT-BASED SENTIMENT ANALYSIS

A method for aspect categorization includes receiving an input text sequence and identifying aspect terms and sentiment phrases in the input text sequence, where present. For an identified aspect term, identifying sentiment dependencies in which the aspect term is in a syntactic dependency with one of the identified sentiment phrases, and identifying pseudo-dependencies from a dependency graph of the input text sequence. The dependency graph includes a sequence of nodes. In a pseudo-dependency, a node representing the aspect term precedes or follows a node representing a semantic anchor in the dependency graph without an intervening other aspect term. Features for the aspect term are extracted from at least one of identified sentiment dependencies and identified pseudo-dependencies. With a classifier trained to output at least one of category labels and polarity labels for aspect terms, classifying the identified aspect term based on the extracted features.