Word embeddings is the representation of the text using vectors such that the words that
have similar syntax and semantic will have similar vector representation. Representing …

Semantic representation reflects the meaning of the text as it may be understood by humans.
Thus, it contributes to facilitating various automated language processing applications …

Keyword extraction is an indispensable step for many natural language processing and
information retrieval applications such as; text summarization and search engine …

Treebanks are valuable linguistic resources that include the syntactic structure of a
language sentence in addition to part-of-speech tags and morphological features. They are …

Automatic keywords extraction is very useful for text summarization, information retrieval and
other natural language applications. This paper proposes a keyword extraction method that …

The improvements of natural language processing applications such as machine translation,
text summarization and the likes are crucial, and can be achieved using many different …

Keywords are commonly used to summarize text documents. In this paper, we perform a
systematic comparison of methods for automatic keyword extraction from web pages. The …

We present a model for automatic extraction of metadata and keywords to be used in the
classification of scientific documents. The model mainly consists of metadata extraction …

Keyphrases are short phrases that best represent a document content. They can be useful in
a variety of applications, including document summarization and retrieval models. In this …

Keyphrase extraction is essential to many Information retrieval (IR) and Natural language
Processing (NLP) tasks such as summarization and indexing. This study investigates deep …