Data deduplication has been widely applied in storage systems to improve the efficiency of space utilization. In data deduplication systems, the data restore performance is seriously hindered by read amplification since the accessed data chunks are scattered over many containers. A container consisting of hundreds or thousands data chunks is the data unit to be read from or write to the storage...

MADlib is an open-source library for scalable in-database analytics. In this paper, we present our parallel design of time series analysis and implementation of ARIMA modeling in MADlib’s framework. The algorithms for fitting time series models are intrinsically sequential since any calculation for a specific time t depends on the result from the previous time step t − 1. Our solution paralleli...

We propose an algorithm for generating all possible generatable r-chunk detectors, which do not cover any elements in self set S. In addition, the algorithm data structure is used to estimate the average number of generatable detectors, dependent on set size S, r-chunk length r and alphabet size Σ. We show that higher alphabets influence the number of generatable detectors in a negative manner.

Ho-Chunk, Inc. is a successful tribal economic development corporation. It is wholly owned by the Winnebago Tribe of Nebraska. The company has won several national awards for excellence in tribal economic development. Due to these awards, over 30 tribes have visited Winnebago. Because of these visits and the system of internal innovation at Ho-Chunk, Inc. a blue print of what a Tribe needs to d...

In our system, we make use of Chunk information to analyze the question. A multilevel method is fulfilled to retrieve candidate Bi-sentences. As to answer selecting, we proposed a voting method. We figure out the performance of each module of our system, and our study shows that 65.54% information has lost in document retrieval and Bi-sentence retrieval. Keyword: Chunk, Bi-sentence, multilevel ...

This paper analyses anaphora from the view of concept association vein. It probes into the problem of sentence semantic chunk share based on the sentence category expression of HNC theory. Firstly, the chunks share is divided into two kinds, one is sharing in a sentence where there is chunk extension into sentence in the sentence, and the other is sharing between two sentences. Secondly, the an...

This paper proposes a new error-driven HMMbased text chunk tagger with context-dependent lexicon. Compared with standard HMM-based tagger, this tagger uses a new Hidden Markov Modelling approach which incorporates more contextual information into a lexical entry. Moreover, an error-driven learning approach is adopted to decrease the memory requirement by keeping only positive lexical entries an...

The structure of a sentence can be seen as a spanning tree in a linguistically augmented graph of syntactic nodes. This paper presents an approach for unlabeled dependency parsing based on this view. The first step involves marking the chunks and the chunk heads of a given sentence and then identifying the intra-chunk dependency relations. The second step involves learning to identify the inter...