Abstract
The paper focuses on using geotagged resources from the social network service (SNS) for searching the famous places from keyword. We extend the HITS[9] algorithm in order to rank locations which are collected from geotagged resources on SNS. Our approach not only uses the similarity measurement between locations’tags for computing the value of locations but also calculate the term frequency of tags which occur in each location to modify the value of tags for ranking. We implement and show the experimental results with the set of locations from the geotagged resources.
Cite
CITATION STYLE
Pham, X. H., Nguyen, T. T., Jung, J. J., & Hwang, D. (2014). Extending HITS algorithm for ranking locations by using geotagged resources. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8733, 332–341. https://doi.org/10.1007/978-3-319-11289-3_34
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
