Generating synopses for document-element search
Sumit Bhatia, Shibamouli Lahiri, Prasenjit Mitra
Abstract
Sumit Bhatia, Shibamouli Lahiri, Prasenjit Mitra
Abstract
Scientists often search for document-elements like tables, figures, or algorithm pseudo-codes. Domain scientists and researchers report important data, results and algorithms using these document-elements; readers want to compare the reported results with their findings. Some document-element search engines have been proposed (especially to search for tables and figures) to make this task easier. While searching for document-elements today, the end-user is presented with the caption of the document-element and a sentence in the document text that refers to the document-element. Oftentimes, the caption and the reference text do not contain enough information to interpret the document-element. In this paper, we present the first set of methods to extract this useful information (synopsis) related to document-elements automatically. We also investigate the problem of choosing the optimum synopsis-size that strikes a balance between information content and size of the generated synopses.
OpenAlex reports 13 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Scientists often search for document-elements like tables, figures, or algorithm pseudo-codes. Domain scientists and researchers report important data, results and algorithms using these document-elements; readers want to compare the reported results with their findings. Some document-element search engines have been proposed (especially to search for tables and figures) to make this task easier. While searching for document-elements today, the end-user is presented with the caption of the document-element and a sentence in the document text that refers to the document-element. Oftentimes, the caption and the reference text do not contain enough information to interpret the document-element. In this paper, we present the first set of methods to extract this useful information (synopsis) related to document-elements automatically. We also investigate the problem of choosing the optimum synopsis-size that strikes a balance between information content and size of the generated synopses.
Key concepts: Computer science, Information retrieval, Element (criminal law), Set (abstract data type), Task (project management), Sentence, Document retrieval, Source document