Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: It is quite common for networks emerging nowadays to have labels or textual contents on the nodes. On such networks,  study the problem of top-k nearest keyword (k-NK) search. In a network G modeled as an undirected graph, each node is attached with zero or more keywords, and each edge is assigned with a ight measuring its length. Given a query node q in G and a keyword λ, a k-NK query seeks k nodes which contain λ and are nearest to q. k-NK is not only useful as a stand-alone query but also as a building block for tackling complex graph pattern matching problems.#R##N##R##N#The key to an accurate k-NK result is a precise shortest distance estimation in a graph. Based on the latest distance oracle technique,  build a shortest path tree for a distance oracle and use the tree distance as a more accurate estimation. With such representation, the original k-NK query on a graph can be reduced to ansring the query on a set of trees and then assembling the results obtained from the trees.  propose two efficient algorithms to report the exact k-NK result on a tree. One is query time optimized for a scenario when a small number of result nodes are of interest to users. The other handles k-NK queries for an arbitrarily large k efficiently. In obtaining a k-NK result on a graph from that on trees, a global storage technique is proposed to further reduce the index size and the query time. Extensive experimental results conform with our theoretical findings, and demonstrate the effectiveness and efficiency of our k-NK algorithms on large real graphs.
['Miao Qiao', 'Lu Qin', 'Hong Cheng', 'Jeffrey Xu Yu', 'Wentao Tian']
I am writing a research paper on a idea Top-K nearest keyword search on large graphs
[{"from": "human", "value": "I am writing a research paper on a idea Top-K nearest keyword search on large graphs"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: It is quite common for networks emerging nowadays to have labels or textual contents on the nodes. On such networks,  study the problem of top-k nearest keyword (k-NK) search. In a network G modeled as an undirected graph, each node is attached with zero or more keywords, and each edge is assigned with a ight measuring its length. Given a query node q in G and a keyword \u03bb, a k-NK query seeks k nodes which contain \u03bb and are nearest to q. k-NK is not only useful as a stand-alone query but also as a building block for tackling complex graph pattern matching problems.#R##N##R##N#The key to an accurate k-NK result is a precise shortest distance estimation in a graph. Based on the latest distance oracle technique,  build a shortest path tree for a distance oracle and use the tree distance as a more accurate estimation. With such representation, the original k-NK query on a graph can be reduced to ansring the query on a set of trees and then assembling the results obtained from the trees.  propose two efficient algorithms to report the exact k-NK result on a tree. One is query time optimized for a scenario when a small number of result nodes are of interest to users. The other handles k-NK queries for an arbitrarily large k efficiently. In obtaining a k-NK result on a graph from that on trees, a global storage technique is proposed to further reduce the index size and the query time. Extensive experimental results conform with our theoretical findings, and demonstrate the effectiveness and efficiency of our k-NK algorithms on large real graphs."}]