Content Recommendation of Tender Documents Based on Qualitative Characteristics

Tingting Zhou (), Guiying Wei () and Ai Wang ()
Additional contact information
Tingting Zhou: University of Science and Technology Beijing
Guiying Wei: University of Science and Technology Beijing
Ai Wang: University of Science and Technology Beijing

A chapter in LISS 2020, 2021, pp 305-321 from Springer

Abstract: Abstract Aiming at content recommendation of tender documents, this paper puts forward the case reuse and case modification algorithm of tender documents. First, according to the usage of clauses in tender cases, this paper uses non-interference sequence index to cluster similar tender cases and similar clauses, then based on which the reference samples and content modules of the tender documents were constructed. Finally, recommended value of reference samples and difference degrees between content modules were used respectively to realize content recommendation. This algorithm ensures the scientificity of the tender documents’ preparation and the accuracy of the recommended content, and greatly improves the efficiency while reducing the scope of the recommended content.

Keywords: Recommendation of tender documents; Case reuse; Case revision; Non-interference sequence index; Reference samples (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-33-4359-7_22

Ordering information: This item can be ordered from
http://www.springer.com/9789813343597

DOI: 10.1007/978-981-33-4359-7_22

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().