Efficient Approximated Matching Methods for Online Incident Data Management

One of major concerns for online traffic information management between data collection and data dissemination is how to effectively deal with data errors from various data sources, e.g., spelling mistakes, truncations, inconsistent conventions and missing fields. The “dirty” input data can be validated and cleaned by being matched against accurate reference databases, before they can be disseminated to the public. This paper proposes two novel approximated matching methods, namely the token based and q-gram based ones for online incident data management. When input records comes in, a relatively small candidate set can be efficiently constructed from records in the large reference table by using the offline pre-built similarity index. The “matched” reference records with highest similarity scores to input ones are found within the candidate set, and can be posted online as clean and accurate information. The experimental results suggest that the proposed approximated matching methods significantly improve data quality and completeness for real time online incident data management.

• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Yang, Fan
• Conference:
  • Transportation Research Board 86th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2007-1-21 to 2007-1-25
• Date: 2007

Language

• English

Media Info

• Media Type: CD-ROM
• Features: Figures; References; Tables;
• Pagination: 15p
• Monograph Title: TRB 86th Annual Meeting Compendium of Papers CD-ROM

Subject/Index Terms

• TRT Terms: Automatic incident detection; Computer online services; Data collection; Driver information systems; Incident detection; Incident management; Information dissemination; Information management; Information processing; Information technology; Validation
• Uncontrolled Terms: Data sources; Online information services; Traffic information
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01043520
• Record Type: Publication
• Report/Paper Numbers: 07-1337
• Files: TRIS, TRB
• Created Date: Feb 8 2007 5:56PM