com.twitter.graphchi.topic_pagerank

PersonalizedPagerank

object PersonalizedPagerank

Computes personalized pagerank for a several "topics" a time. Input: a list of files containing list of vertex-ids with non-zero reset probability for a topic. TODO: improve doc.

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Type Members

  1. case class TopicInfo(topicName: String, seedFile: String) extends Product with Serializable

Value Members

  1. final def !=(arg0: AnyRef): Boolean

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  2. final def !=(arg0: Any): Boolean

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  3. final def ##(): Int

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  4. final def ==(arg0: AnyRef): Boolean

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  5. final def ==(arg0: Any): Boolean

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  6. val RESETPROB: Float

  7. final def asInstanceOf[T0]: T0

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  8. def clone(): AnyRef

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  9. final def eq(arg0: AnyRef): Boolean

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  10. def equals(arg0: Any): Boolean

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  11. def finalize(): Unit

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    protected[java.lang]
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  12. final def getClass(): Class[_]

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  13. def hashCode(): Int

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  14. def initVertexData[T](graphname: String, graphchiSqr: GraphChiSquared[T]): Unit

  15. def initialize(initfile: String): Int

  16. final def isInstanceOf[T0]: Boolean

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  17. def main(args: Array[String]): Unit

  18. final def ne(arg0: AnyRef): Boolean

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  19. final def notify(): Unit

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  20. final def notifyAll(): Unit

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  21. def resetProbability(v: VertexInfo[Integer, Float], computationId: Int, numVertices: Int): Float

  22. final def synchronized[T0](arg0: ⇒ T0): T0

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  23. def toString(): String

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  24. var topicInfos: Array[TopicInfo]

  25. final def wait(): Unit

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  26. final def wait(arg0: Long, arg1: Int): Unit

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  27. final def wait(arg0: Long): Unit

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