Nitrogen-rich isoindoline-based porous polymer: Promoting knoevenagel reaction at room temperature

Nitrogen-rich porous organic polymers(POPs)with basic features have already shown promising performance in various organic reactions.But the harsh conditions,tedious synthetic methods and the requirement of specific monomers impede their further application.Herein,we introduce isoindoline chemistry into POP community.An isoindoline formation process between aniline and bromomethylbenzenedcoupling nucleophilic substitution,HBr elimination,and intramolecular cyclization in one pot,is utilized for POPs synthesis.Nitrogen-rich isoindolinebased porous polymers(IPPs)were obtained with specific surface areas up to 408 m^(2) g^(-1).Unexpectedly,mechanochemistry could enable the rapid(3 h)and solid-state synthesis of IPP catalysts.Moreover,this nitrogen-rich catalyst presents excellent activity(isolated yield:99%),scalable ability(up to 14 g per run)and recyclability(five runs)towards the Knoevenagel condensation reaction under mild reaction conditions(water as solvent at room temperature).

Group relational privacy protection on time-constrained point of interests

1 Introduction With the rapid development of mobile networks,locationbased services has become popular in the daily lives of people.The service providers can recommend the profitable services to persons through mining the frequent interests or places of persons.However,one aspect is that the historical data on Internet can easily cause the leakage of user-relationship privacy,another aspect is that the historical interests of person are always bound to time.Therefore,this paper devotes to study a privacy protection method on time-constrained point of interests(PoIs)based on the group relationships of users.

A subgraph matching algorithm based on subgraph index for knowledge graph

The problem of subgraph matching is one fundamental issue in graph search,which is NP-Complete problem.Recently,subgraph matching has become a popular research topic in the field of knowledge graph analysis,which has a wide range of applications including question answering and semantic search.In this paper,we study the problem of subgraph matching on knowledge graph.Specifically,given a query graph q and a data graph G,the problem of subgraph matching is to conduct all possible subgraph isomorphic mappings of q on G.Knowledge graph is formed as a directed labeled multi-graph having multiple edges between a pair of vertices and it has more dense semantic and structural features than general graph.To accelerate subgraph matching on knowledge graph,we propose a novel subgraph matching algorithm based on subgraph index for knowledge graph,called as FGqT-Match.The subgraph matching algorithm consists of two key designs.One design is a subgraph index of matching-driven flow graph(FGqT),which reduces redundant calculations in advance.Another design is a multi-label weight matrix,which evaluates a near-optimal matching tree for minimizing the intermediate candidates.With the aid of these two key designs,all subgraph isomorphic mappings are quickly conducted only by traversing FGqj.Extensive empirical studies on real and synthetic graphs demonstrate that our techniques outperform the state-of-the-art algorithms.