The availability of legal judgment documents in digital form offers numerous opportunities for
information extraction and application. Automatic summarization of these legal texts is a …

Text generation is an essential research area in artificial intelligence (AI) technology and
natural language processing and provides key technical support for the rapid development …

The representation of words in the vector space generated using the Word2Vec model does
not capture the syntactic similarity between sentences, but only the semantic similarity by …

Users are increasingly empowered to personalize natural language interfaces (NLIs) by
teaching how to handle new natural language (NL) inputs. However, our formative study …

Machine learning often requires millions of examples to produce static, black-box models. In
contrast, interactive task learning (ITL) emphasizes incremental knowledge acquisition from …

In recent years, with the development of the social Internet of Things (IoT), all kinds of data
accumulated on the network. These data, which contain a lot of social information and …

The similarity between two sentences is the score that represents the relatedness and
likelihood between those sentences. Measuring sentence similarity has attracted …

Large texts are not always entirely meaningful: they might include repetitions and useless
details, and might not be easy to interpret by humans. Automatic text summarization aims to …

Semantic textual similarity methods are becoming increasingly crucial in text mining
research areas such as text retrieval and summarization. Existing methods of text similarity …

Sentence similarity is widely used in various natural language tasks such as natural
language inference, paraphrase identification, and question answering. However, a variety …