Abstract
Spatial database are becoming more and more popular in recent years. There is more and more commercial and research interest in location-based search from spatial database. Spatial keyword search has been well studied for years due to its importance to commercial search engines. Specially, a spatial keyword query takes a user location and user-supplied keywords as arguments and returns objects that are spatially and textually relevant to these arguments. Geo-textual index play an important role in spatial keyword querying. A number of geo-textual indices have been proposed in recent years which mainly combine the R-tree and its variants and the inverted file. This paper propose new index structure that combine K-d tree and inverted file for spatial range keyword query which are based on the most spatial and textual relevance to query point within given range.
Highlights
Spatial data are data that have a location and mainly required for Geographic Information Systems (GIS) whose information is related to geographic locations
The query consists of a spatial location, a set of keywords and a parameter k and the answer is a list of objects ranked according to a combination of their distance to the query point and the relevance of their text description to the query keyword
The spatial relevance is measured by the distance between the location associated with the candidate document to the query location, and the textual relevance is said to be textually relevant to a query if object contains queried keywords. [1]
Summary
Spatial data are data that have a location (spatial) and mainly required for Geographic Information Systems (GIS) whose information is related to geographic locations. All use R-tree for spatial (latitude/longitude) index and inverted file for textual index. They all created hybrid index structure according to the combination schemes: (1) Text first loose combination scheme, employs the inverted as the top-level index and arrange the postings in each inverted list in a spatial structure. This paper includes the following contributions: 1) The main contribution is to create index structure that combine K-d tree and inverted file for efficiently process spatial keyword queries within minimum time. 2) Range keyword search algorithm is developed using the proposed index structure to efficiently answer Boolean range queries and to explore useful and exact information that user required. 3) The own dataset is created for Yangon (Myanmar) region which contains latitude, longitude, name, description and category type of each object
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Computer Science & Engineering: An International Journal
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
