Ranking and Mapping of Hotels & Restaurants efficient keywords prediction
Abstract: Keyword queries on databases provide easy access to data, but often suffer from low ranking quality, i.e., low precision and/or recall, as shown in recent benchmarks. It would be useful to identify queries that are likely to have low ranking quality to improve the user satisfaction. For instance, the system may suggest to the user alternative queries for such hard queries. In this paper, we analyze the characteristics of hard queries and propose a novel framework to measure the degree of difficulty for a keyword query over a database, considering both the structure and the content of the database and the query results. We evaluate our query difficulty prediction model against one effectiveness benchmarks for popular keyword search ranking methods. Our empirical results show that our model predicts the hard queries with high accuracy. Further, we present a suite of optimizations to minimize the incurred time overhead. We also provide mapping methodology for hotels and restaurants which will be used for getting directions with the help of Google Maps.
Keywords: Query performance, query effectiveness, keyword query, robustness, databases,Google Maps.
How to Cite:
[1] Prof. Reena mahe, Abhijeet Javlekar, Pratik Dabholakar, Madhav Kantak, Jayesh Dhawase, “Ranking and Mapping of Hotels & Restaurants efficient keywords prediction,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2016.5460
