This paper presents a memory−based model of human syntactic processing: Data−Oriented Parsing. After a brief introduction (section 1), it argues that any account of disambiguation and many other performance phenomena inevitably has an important memory−based component (section 2). It discusses the limitations of probabilistically enhanced competence−grammars, and argues for a more principled mem...

We discuss a novel two-dimensional parallel technique for reliable data detection in page-oriented optical memories. The method is motivated by decision feedback techniques and is fully parallel, offering convenient, locally connected electronic implementation. The algorithm is shown to offer significant improvements over simple threshold detection and in some cases can approach the maximum-lik...

With growing of memory capacity, to detect memory faults is more and more difficult, and its cost increases rapidly. Since these faults seriously decrease the yield rate of memories, it is necessary to find an effective test algorithm for memory to improve the chip yield rate. In these days, as word-oriented memories are broadly used, testing for word-oriented memory becomes more important. In ...

Current web mining approaches use massive amounts of commodity hardware and processing time to leverage analytics for today’s web. For a seamless application interaction, those approaches have to use pre-aggregated results and indexes to circumvent the slow processing on their data stores e.g. relational databases or document stores. The upcoming trend of in-memory, column-oriented databases is...

In this paper we describe a storage system called Violet that efficiently marries fine-grained host side data management with capacity optimized backend disk systems. Currently, for efficiency reasons, real-time analytics applications are forced to map their in-memory graph like data structures on to columnar databases or other intermediate disk friendly data structures when they are persisting...