In entity-relation (ER) graphs (V, E), nodes V represent typed entities and edges E represent typed relations. For dynamic personalized PageRank queries, nodes are ranked by their steady-state probabilities obtained using the standard random surfer model. In this work, we propose a framework to answer top-k graph conductance queries. Our top-k ranking technique leads to a 4× speedup, and overall, our system executes queries 200-1600× faster than whole-graph PageRank. Some queries might contain hard predicates i.e. predicates that must be satisfied by the answer nodes. E.g., we may seek authoritative papers on public key cryptography, but only those written during 1997. We extend our system to handle hard predicates. Our system achieves these substantial query speedups while consuming only 10-20% of the space taken by a regular text index.

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This study describes a method for the composition analysis of the carbon black-filled polychloroprene rubber (CR) compound. Good agreement of the experimental data with the actual value was found. The method is based on three experiments namely thermogravimetric analysis, solvent extraction, and newly developed thermo and thermo-oxidative degradation of the vulcanized CR compound in the presence of nickel catalyst. Thermogravimetric analysis experiment gives the amount of inorganic material in the rubber compound. Solvent extraction gives the extractable amount. Thermo-oxidative degradation experiment gives the polymer amount. In thermo-oxidative degradation experiment, liberated chloride ion was titrated by Mohr’s method, and the amount of CR was back calculated from the chlorine content.