Geoportal with Recommendation Capability

Abstract:
As the number of published geospatial resources in the web is increasing permanently, providing users with proper tools for search and discovery of these resource is of great importance. Geoportals are a type of web portals that enable users to find geospatial resources. However, when users search for a specific resource in existing geoportals, a wide range of unrelated results might be retrieved. Such results are often confusing, so that user has to spend a lot of time to find the most appropriate resource. In addition, working based on user desires and preferences has been considered as a fundamental characteristic of modern web applications.
In this article, the capability of recommendation is added to the geoportal. The recommendation capability enhances the ability of geoportals which is able to recommend the most appropriate geospatial resources to users by considering their desires and preferences. In order to accomplish this purpose, a new solution with recommender systems is proposed. Recommender systems using knowledge derived from the users’ previous interactions can lead users to access resources that they are interested in. Collaborative filtering is a common technique used in recommender systems that deal with this problem. This method uses user rating data to extract the similarity between users or resources for making recommendations. Moreover, mathematical functions are defined in order to improve the efficiency of the recommender geoportal process. The functions are designed according to the specifications of users and resources such as city, county and language, along with the distance between the user and resource.
In addition, an operation of these functions is to obviate the cold-start problem in collaborative filtering. To evaluate the designed geoportal recommender, a recommender geoportal is implemented so that a user is able to profit the advantages and usage of its recommendations. The obtained results indicate that the efficiency of recommender geoportals is improved compared with common geoportals.
Language:
Persian
Published:
Journal of Geomatics Science and Technology, Volume:5 Issue: 4, 2016
Pages:
155 to 171
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