Dewey Code Research Articles

The application of agglomerative hierarchical spatial clustering algorithm in tea blending

Playing a significant role in production process of tea enterprise, tea blending has advantages in improving the quality of tea, expanding resource of tea, and getting higher profits. Traditional manual blending method not merely wastes time and energy but also has difficulties in optimizing blending programs. In this paper, tea blending problem is modeled as spatial clustering based on multi-dimensional hierarchy space. Tea attributes such as varieties of tea bush, process crafts and producing areas are modeled into hierarchy space with tree structure. Every node of these trees is present a value of tea attributes. So all the data tuples are mapped as points in multi-dimensional hierarchy space. And we define a similarity-based measure criterion in multi-dimensional conceptual layered space to present an agglomerative hierarchical spatial clustering based algorithm to work out the optimal blending program. Meanwhile, Dewey code is introduced to increase resolution efficiency. Dewey code is used presented the points in hierarchy space, and the codes of every point can be adopted to compute the similarity of every two points in the measure criterion. Two clustering algorithms have been proposed. We agglomerate two points which are the closest to each other according to the similarity measure criterion in hierarchy space by algorithm AGHC. In DIHC, the whole dataset is divided into small parts through K-medios until there are N clusters and N is set by users. Tea attributes are quantified and the process of tea blending is standardized. This study enable tea blending to get rid of human experience, instead of intelligent approach. The results of tea blending in this article can be accurate due to the strict consolidation doctrine. That means we will be rational when we choose which tea to be blended in practice to satisfy customers’ demands. Appropriate tea will be blended by several kinds of tea with the study in this article. Finally, experiments on real data set demonstrate the solution of tea blending proposed in this paper is greatly improving work efficiency and economic benefits.

FSPTwigFast: Holistic twig query on fuzzy spatiotemporal XML data

With spatiotemporal applications increasing, a large amount of spatiotemporal data emerges. Because temporal and spatial attributes are often vague, research on fuzzy spatiotemporal data, especially querying fuzzy spatiotemporal data, has attracted a lot of attention. However, although fuzzy logic is incorporated in querying fuzzy spatiotemporal data and querying fuzzy data in XML, relatively little work has been carried out in querying fuzzy spatiotemporal data in XML. In this paper, we propose an algorithm, called FSPTwigFast, to match fuzzy spatiotemporal XML twig pattern. We represent fuzzy spatiotemporal data by adding temporal and spatial attributes associating with fuzziness in crisp data. We extend Dewey code to mark fuzzy spatiotemporal data for special process and determine structure relationship of fuzzy spatiotemporal nodes in XML documents. Our technique uses streams to store leaf nodes in XML document corresponding to leaf query nodes, which are filtered to delete unmatched nodes. After filtering, output lists are built for every matched leaf node. Finally, the experimental results demonstrate the performance advantages of our approach.

Efficiently querying dynamic XML documents stored in relational database systems

Storing XML documents in relational database systems has become a widely used solution. However, in the process of shredding and indexing the XML document, the use of special labelling methods to recover the document order is still required in order to efficiently support data-centric queries and update operations (e.g., the addition and deletion of nodes from the document). In this paper, we present a new space-efficient labelling scheme based on Dewey codes. The new label structure, which is composed of parent-child components in the Dewey format, would significantly improve the performance of XML queries that are based on parent-child and sibling relationships. Furthermore, we introduce an alternative approach to validate ancestor relationships and to navigate upwards in XML trees efficiently. We report on an extensive experimental evaluation using several well-known XML benchmarks for the comparison of the impact of our approach on label length and query performance against those of some other recent Dewey-based approaches.

Research and design of querying approach for XML encrypted data

The structural characteristics of XML database document have been fully made use of and combined with the encoding theory of Dewey code to design an encrypted XML algorithm called Index Layered Itersection Scan Algorithm(ILISA)under the model of Database as A Service(DAS).The data retrieval of tree structure was turned into the data retrieval of sequential list form.The authors applied the interpolation search algorithm instead of depth-first or breadth-first search,which had brought a good time complexity.And a data structure of XML index table was designed to reduce the search space greatly.Finally,the complexity of ILISA was described and the efficiency of ILISA was proved.

SAIL: Structure-aware indexing for effective and progressive top- k keyword search over XML documents

Keyword search in XML documents has recently gained a lot of research attention. Given a keyword query, existing approaches first compute the lowest common ancestors (LCAs) or their variants of XML elements that contain the input keywords, and then identify the subtrees rooted at the LCAs as the answer. In this the paper we study how to use the rich structural relationships embedded in XML documents to facilitate the processing of keyword queries. We develop a novel method, called SAIL, to index such structural relationships for efficient XML keyword search. We propose the concept of minimal-cost trees to answer keyword queries and devise structure-aware indices to maintain the structural relationships for efficiently identifying the minimal-cost trees. For effectively and progressively identifying the top- k answers, we develop techniques using link-based relevance ranking and keyword-pair-based ranking. To reduce the index size, we incorporate a numbering scheme, namely schema-aware dewey code, into our structure-aware indices. Experimental results on real data sets show that our method outperforms state-of-the-art approaches significantly, in both answer quality and search efficiency.

Layered Solution for SLCA Problem in XML Information Retrieval

SLCA (smallest lowest common ancestor) problem is a basic task of keyword search in XML information retrieval. It means to find all the nodes corresponding to the tightest subtrees in XML data, which involves the given keywords. Xu, et al., illustrate three algorithms—Indexed lookup eager (ILE), stack algorithm and scan eager (SE), and manifest that ILE has the best performance. Different from the complicated-B+-tree-based ILE algorithm, this paper proposes a layered solution for SLCA problem, named as LISA (layered intersection scan algorithm). It benefits from the distribution rule of SLCA nodes in XML tree, and calculates the SLCA nodes level by level (the deepest level runs first). That is, based on the retrieved Dewey codes corresponding to given keywords, the Dewey codes of SLCA nodes can be gotten by intersecting the prefix Dewey codes of each level. Compared with the ILE algorithm, LISA solutions need not sophisticated data structures, and have comparatively runtime performance. There are two instances following the LISA idea, called LISA I and LISA II respectively. They are distinguished from each other according to whether keeping Dewey codes in computation or transforming Dewey codes into integer sequences. Extensive experiments evaluate the performance of algorithms and prove the efficiency of LISA II.

Developing a Classroom Community of Interpreters

Eleventh grade honors English had been taught for years by a closet librarian, a tall, striking woman, happier among file cards and Dewey codes than with pimply faces and awkward adolescent attempts at explications of Paradise Lost. Stories were told that her test on Canterbury Tales asked questions like Which character had a wart on the left side of her nose? And not to be funny. So when our schedules showed a different set