Keyphrase Generation for Scientific Document Retrieval
Sequence-to-sequence models have lead to significant progress in keyphrase generation, but it remains unknown whether they are reliable enough to be beneficial for document retrieval. This study provides empirical evidence that such models can significantly improve retrieval performance, and introduces a new extrinsic evaluation framework that allows for a better understanding of the limitations of keyphrase generation models. Using this framework, we point out and discuss the difficulties encountered with supplementing documents with -- not present in text -- keyphrases, and generalizing models across domains. Our code is available at https://github.com/boudinfl/ir-using-kg
Code (1)
Tasks
Keyphrase GenerationRetrievalSimilar Papers 제목 키워드 기반
Redefining Absent Keyphrases and their Effect on Retrieval Effectiveness
Neural keyphrase generation models have recently attracted much interest due to their ability to output absent keyphrases, that is, keyphrases that do not appear in the source text. In this paper, we discuss the usefulne…
Information RetrievalKeyphrase GenerationRetrievalLDKP: A Dataset for Identifying Keyphrases from Long Scientific Documents
Identifying keyphrases (KPs) from text documents is a fundamental task in natural language processing and information retrieval. Vast majority of the benchmark datasets for this task are from the scientific domain contai…
ArticlesInformation RetrievalKeyphrase ExtractionKeyphrase Generation+1Deep Keyphrase Completion
Keyphrase provides accurate information of document content that is highly compact, concise, full of meanings, and widely used for discourse comprehension, organization, and text retrieval. Though previous studies have m…
DecoderKeyphrase ExtractionKeyphrase GenerationRetrieval+1TA-DA: Topic-Aware Domain Adaptation for Scientific Keyphrase Identification and Classification (Student Abstract)
Keyphrase identification and classification is a Natural Language Processing and Information Retrieval task that involves extracting relevant groups of words from a given text related to the main topic. In this work, we …
Domain AdaptationInformation RetrievalKeyphrase ExtractionMulti-Task Learning+1Keyphrase Extraction from Scientific Articles via Extractive Summarization
Automatically extracting keyphrases from scholarly documents leads to a valuable concise representation that humans can understand and machines can process for tasks, such as information retrieval, article clustering and…
ArticlesExtractive SummarizationInformation RetrievalKeyphrase Extraction+1