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Ranking and Mapping of Hotels & Restaurants using Approximation Algorithm


Abhijeet Vijay Javlekar , Atharva College Of Engineering Mumbai, Maharashtra, India; Pratik Hemant Dabholkar, Atharva College Of Engineering Mumbai, Maharashtra, India; Madhav Manjunath Kantak, Atharva College Of Engineering Mumbai, Maharashtra, India; Jayesh Vijay Dhawase, Atharva College Of Engineering Mumbai, Maharashtra, India


Query performance, query effectiveness, keyword query, robustness, databases,Google Maps


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.

Other Details

Paper ID: NCTAAP141
Published in: Conference 4 : NCTAA 2016
Publication Date: 29/01/2016
Page(s): 607-609

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