LDkp (Long Document keyphrase) dataset is the first benchmark corpus of 1.3M documents for identifying keyphrases from long documents.The LDkp dataset is released in two versions : LDkp3k consists of 0.1M keyphrase tagged long documents, is created using keyphrases from KP20k (Meng et al., 2017) and their corresponding long document text from S2ORC (Lo et al., 2020). LDkp10k consists of 1.3M long documents along with target keyphrases is created using keyphrases from OAGKX (Çano, 2019) and their corresponding long document text from S2ORC (Lo et al., 2020)
Keywords and keyphrases have many useful roles as document surrogates and descriptors, but the manua...
Keyphrases can provide a brief summary of documents. Keyphrase extraction, defined as automatic sele...
In this work, we explore how to learn task-specific language models aimed towards learning rich repr...
Keyphrases provide semantic metadata that summarize and characterize documents. This paper describes...
Transformer-based architectures in natural language processing force input size limits that can be p...
OAGK is a keyword extraction/generation dataset consisting of 2.2 million abstracts, titles and keyw...
The keyphrases of a document are the textual units that characterize its content such as the topics ...
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Com...
International audienceKeyphrase generation is the task of predicting a set of lexical units that con...
The automatic keyphrases extraction (AKE) of a document is any expression by which we can learn its ...
International audienceState of the art of deep learning methods for automatic keyphrase extraction T...
Automatic keyphrases extraction (AKE) is a principal task in natural language processing (NLP). Seve...
Keyphrases are an important means of document summarization, clustering, and topic search. Only a sm...
Keyphrases can provide a brief summary of documents. Keyphrase extraction, defined as automatic sele...
Keyphrase extraction aims to find representative phrases for a document. Keyphrases are expected to ...
Keywords and keyphrases have many useful roles as document surrogates and descriptors, but the manua...
Keyphrases can provide a brief summary of documents. Keyphrase extraction, defined as automatic sele...
In this work, we explore how to learn task-specific language models aimed towards learning rich repr...
Keyphrases provide semantic metadata that summarize and characterize documents. This paper describes...
Transformer-based architectures in natural language processing force input size limits that can be p...
OAGK is a keyword extraction/generation dataset consisting of 2.2 million abstracts, titles and keyw...
The keyphrases of a document are the textual units that characterize its content such as the topics ...
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Com...
International audienceKeyphrase generation is the task of predicting a set of lexical units that con...
The automatic keyphrases extraction (AKE) of a document is any expression by which we can learn its ...
International audienceState of the art of deep learning methods for automatic keyphrase extraction T...
Automatic keyphrases extraction (AKE) is a principal task in natural language processing (NLP). Seve...
Keyphrases are an important means of document summarization, clustering, and topic search. Only a sm...
Keyphrases can provide a brief summary of documents. Keyphrase extraction, defined as automatic sele...
Keyphrase extraction aims to find representative phrases for a document. Keyphrases are expected to ...
Keywords and keyphrases have many useful roles as document surrogates and descriptors, but the manua...
Keyphrases can provide a brief summary of documents. Keyphrase extraction, defined as automatic sele...
In this work, we explore how to learn task-specific language models aimed towards learning rich repr...