Модель Классификации

Web extraction systems attempt to use the immense amount of unlabeled text in the Web in order to create large lists of entities and relations. Unlike traditional IE methods, the …...

. In this paper, we introduce a minimally supervised method for learning to classify named-entity titles in a given encyclopedia into broad semantic categories in an existing ontology. Our main …...

AbstractThe paper presents an innovative approach to extract Slovene definition candidates from domain-specific corpora using morphosyntactic patterns, automatic terminology recognition and semantic tagging with wordnet senses. First, a classification model …...

In this paper, we introduce a tripartite scheme for the classification of intransitive verbs for Hindi and claim it to be a more suitable model of classification than the classical …...

We present a classification model that predicts the presence or omission of a lexical connec- tive between two clauses, based upon linguis- tic features of the clauses and the type …...

Derivationally related lemmas like friendN – friendlyA – friendshipN are derived from a common stem. Frequently, their meanings are also systematically related. However, there are also many examples of derivationally …...

AbstractWebsites’ and mobile apps’ privacy policies, written in natural language, tend to be long and difficult to understand. Information privacy revolves around the fundamental principle of Notice and choice, namely …...

AbstractLexical ambiguity can impede NLP systems from accurate understanding of semantics. Despite its potential benefits, the integration of sense-level information into NLP systems has remained understudied. By incorporating a novel …...

AbstractIn realistic scenarios, a user profiling model (e.g., gender classification or age regression) learned from one social media might perform rather poorly when tested on another social media due to …...

AbstractMovies help us learn and inspire societal change. But they can also contain objectionable content that negatively affects viewers’ behaviour, especially children. In this paper, our goal is to predict …...

AbstractDetecting public sentiment drift is a challenging task due to sentiment change over time. Existing methods first build a classification model using historical data and subsequently detect drift if the …...

AbstractIdentifying statements related to suicidal behaviour in psychiatric electronic health records (EHRs) is an important step when modeling that behaviour, and when assessing suicide risk. We apply a deep neural …...

AbstractWe study the problem of generating counterfactual text for a classifier as a means for understanding and debugging classification. Given a textual input and a classification model, we aim to …...

AbstractExtracting spatial relations from texts is a fundamental task for natural language understanding and previous studies only regard it as a classification task, ignoring those spatial relations with null roles …...

AbstractCommonsense knowledge about the typicalfunctions of physical objects allows people tomake inferences during sentence understanding. For example, we infer that “Sam enjoyedthe book” means that Sam enjoyed reading thebook, even …...