In information retrieval systems, the location information can be collected by using Global Positioning Systems for providing Location Based Services (LBS) to the information system users. The LBS can be either person-oriented or device-oriented. In the person-oriented approach, the LBS focuses on the location of the user and the user can control the services provided by the service provider. In the device-oriented approach, the LBS focuses on the object and it is not controlled by the mobile user. The LBS also manages Points of Interest (POI) of mobile users in order to perform effective route finding for providing the services fast. Moreover, the users of mobile devices tend to query based on Points of Interest such as for restaurants and markets where the users can query based on its attributes like price, type of food, user ratings which are close to their current location. The POI is calculated primarily on the interest of mobile users and the ratings given by existing user’s with their feedback. The users can select the features to obtain specific objects. In this paper, a new information retrieval model is proposed for improving the performance of information systems by providing new data structures and algorithms for storage and retrieval of data. The primary idea behind this work is to minimize the number of user requests and to achieve high accuracy for the user’s query result by using an information repository called as the Path Log. The Path Log is used to store the information about the search time and distance of the service provider locations by providing an optimal route to serve the users information request. For this purpose, a new spatial indexing is used in this work to obtain an accurate and optimal path to reach the location of the services. The tree has been constructed by giving weights for the leaf nodes. Thus the solution proposed in this work for providing LBS is achieved by processing the K-Nearest Neighbor and Range queries such that the user requests for information retrieval is carried out more optimally. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.