990 resultados para Top-K
Resumo:
With the proliferation of geo-positioning and geo-tagging techniques, spatio-textual objects that possess both a geographical location and a textual description are gaining in prevalence, and spatial keyword queries that exploit both location and textual description are gaining in prominence. However, the queries studied so far generally focus on finding individual objects that each satisfy a query rather than finding groups of objects where the objects in a group together satisfy a query.
We define the problem of retrieving a group of spatio-textual objects such that the group's keywords cover the query's keywords and such that the objects are nearest to the query location and have the smallest inter-object distances. Specifically, we study three instantiations of this problem, all of which are NP-hard. We devise exact solutions as well as approximate solutions with provable approximation bounds to the problems. In addition, we solve the problems of retrieving top-k groups of three instantiations, and study a weighted version of the problem that incorporates object weights. We present empirical studies that offer insight into the efficiency of the solutions, as well as the accuracy of the approximate solutions.
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Massive amount of data that are geo-tagged and associated with text information are being generated at an unprecedented scale. These geo-textual data cover a wide range of topics. Users are interested in receiving up-to-date geo-textual objects (e.g., geo-tagged Tweets) such that their locations meet users’ need and their texts are interesting to users. For example, a user may want to be updated with tweets near her home on the topic “dengue fever headache.” In this demonstration, we present SOPS, the Spatial-Keyword Publish/Subscribe System, that is capable of efficiently processing spatial keyword continuous queries. SOPS supports two types of queries: (1) Boolean Range Continuous (BRC) query that can be used to subscribe the geo-textual objects satisfying a boolean keyword expression and falling in a specified spatial region; (2) Temporal Spatial-Keyword Top-k Continuous (TaSK) query that continuously maintains up-to-date top-k most relevant results over a stream of geo-textual objects. SOPS enables users to formulate their queries and view the real-time results over a stream of geotextual objects by browser-based user interfaces. On the server side, we propose solutions to efficiently processing a large number of BRC queries (tens of millions) and TaSK queries over a stream of geo-textual objects.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Spatial data mining recently emerges from a number of real applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. In this paper, we investigate the problem of evaluating the top k distinguished “features” for a “cluster” based on weighted proximity relationships between the cluster and features. We measure proximity in an average fashion to address possible nonuniform data distribution in a cluster. Combining a standard multi-step paradigm with new lower and upper proximity bounds, we presented an efficient algorithm to solve the problem. The algorithm is implemented in several different modes. Our experiment results not only give a comparison among them but also illustrate the efficiency of the algorithm.
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Graph-structured databases are widely prevalent, and the problem of effective search and retrieval from such graphs has been receiving much attention recently. For example, the Web can be naturally viewed as a graph. Likewise, a relational database can be viewed as a graph where tuples are modeled as vertices connected via foreign-key relationships. Keyword search querying has emerged as one of the most effective paradigms for information discovery, especially over HTML documents in the World Wide Web. One of the key advantages of keyword search querying is its simplicity—users do not have to learn a complex query language, and can issue queries without any prior knowledge about the structure of the underlying data. The purpose of this dissertation was to develop techniques for user-friendly, high quality and efficient searching of graph structured databases. Several ranked search methods on data graphs have been studied in the recent years. Given a top-k keyword search query on a graph and some ranking criteria, a keyword proximity search finds the top-k answers where each answer is a substructure of the graph containing all query keywords, which illustrates the relationship between the keyword present in the graph. We applied keyword proximity search on the web and the page graph of web documents to find top-k answers that satisfy user’s information need and increase user satisfaction. Another effective ranking mechanism applied on data graphs is the authority flow based ranking mechanism. Given a top- k keyword search query on a graph, an authority-flow based search finds the top-k answers where each answer is a node in the graph ranked according to its relevance and importance to the query. We developed techniques that improved the authority flow based search on data graphs by creating a framework to explain and reformulate them taking in to consideration user preferences and feedback. We also applied the proposed graph search techniques for Information Discovery over biological databases. Our algorithms were experimentally evaluated for performance and quality. The quality of our method was compared to current approaches by using user surveys.
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We build a system to support search and visualization on heterogeneous information networks. We first build our system on a specialized heterogeneous information network: DBLP. The system aims to facilitate people, especially computer science researchers, toward a better understanding and user experience about academic information networks. Then we extend our system to the Web. Our results are much more intuitive and knowledgeable than the simple top-k blue links from traditional search engines, and bring more meaningful structural results with correlated entities. We also investigate the ranking algorithm, and we show that the personalized PageRank and proposed Hetero-personalized PageRank outperform the TF-IDF ranking or mixture of TF-IDF and authority ranking. Our work opens several directions for future research.
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With the exponential growth of the usage of web-based map services, the web GIS application has become more and more popular. Spatial data index, search, analysis, visualization and the resource management of such services are becoming increasingly important to deliver user-desired Quality of Service. First, spatial indexing is typically time-consuming and is not available to end-users. To address this, we introduce TerraFly sksOpen, an open-sourced an Online Indexing and Querying System for Big Geospatial Data. Integrated with the TerraFly Geospatial database [1-9], sksOpen is an efficient indexing and query engine for processing Top-k Spatial Boolean Queries. Further, we provide ergonomic visualization of query results on interactive maps to facilitate the user’s data analysis. Second, due to the highly complex and dynamic nature of GIS systems, it is quite challenging for the end users to quickly understand and analyze the spatial data, and to efficiently share their own data and analysis results with others. Built on the TerraFly Geo spatial database, TerraFly GeoCloud is an extra layer running upon the TerraFly map and can efficiently support many different visualization functions and spatial data analysis models. Furthermore, users can create unique URLs to visualize and share the analysis results. TerraFly GeoCloud also enables the MapQL technology to customize map visualization using SQL-like statements [10]. Third, map systems often serve dynamic web workloads and involve multiple CPU and I/O intensive tiers, which make it challenging to meet the response time targets of map requests while using the resources efficiently. Virtualization facilitates the deployment of web map services and improves their resource utilization through encapsulation and consolidation. Autonomic resource management allows resources to be automatically provisioned to a map service and its internal tiers on demand. v-TerraFly are techniques to predict the demand of map workloads online and optimize resource allocations, considering both response time and data freshness as the QoS target. The proposed v-TerraFly system is prototyped on TerraFly, a production web map service, and evaluated using real TerraFly workloads. The results show that v-TerraFly can accurately predict the workload demands: 18.91% more accurate; and efficiently allocate resources to meet the QoS target: improves the QoS by 26.19% and saves resource usages by 20.83% compared to traditional peak load-based resource allocation.
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The subthreshold slope, transconductance, threshold voltage, and hysteresis of a carbon nanotube field-effect transistor (CNT FET) were examined as its configuration was changed from bottom-gate exposed channel, bottom-gate covered channel to top-gate FET. An individual single wall CNT was grown by chemical vapor deposition and its gate configuration was changed while determining its transistor characteristics to ensure that the measurements were not a function of different chirality or diameter CNTs. The bottom-gate exposed CNT FET utilized 900 nm SiO2 as the gate insulator. This CNT FET was then covered with TiO2 to form the bottom-gate covered channel CNT FET. Finally, the top-gate CNT FET was fabricated and the device utilized TiO 2 (K ∼ 80, equivalent oxide thickness=0.25 nm) as the gate insulator. Of the three configurations investigated, the top-gate device exhibited best subthreshold slope (67-70 mV/dec), highest transconductance (1.3 μS), and negligible hysteresis in terms of threshold voltage shift. © 2006 American Institute of Physics.
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YBaCuO and GdBaCuO + 15 wt% Ag large, single-grain, bulk superconductors have been fabricated via the top-seeded, melt-growth (TSMG) process using a generic NdBCO seed. The mechanical behavior of both materials has been investigated by means of three-point bending (TPB) and transversal tensile tests at 77 and 300 K. The strength, fracture toughness and hardness of the samples were studied for two directions of applied load to obtain comprehensive information about the effect of microstructural anisotropy on the macroscopic and microscopic mechanical properties of these technologically important materials. Splitting (Brazilian) tests were carried out on as-melt-processed cylindrical samples following a standard oxygenation process and with the load applied parallel to the growth-facet lines characteristic of the TSMG process. In addition, the elastic modulus of each material was measured by three different techniques and related to the microstructure of each sample using optical microscopy. The results show that both the mechanical properties and the elastic modulus of both YBCO and GdBCP/Ag are improved at 77 K. However, the GdBCO/Ag samples are less anisotropic and exhibit better mechanical behavior due to the presence of silver particles in the bulk, superconducting matrix. The splitting tensile strength was determined at 77 K and both materials were found to exhibit similar behavior, independently of their differences in microstructure.
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Polymerase chain reaction (PCR) was developed for the detection of Banana bunchy top virus (BBTV) at maximum after 210 min and at minimum after 90 min using Pc-1 and Pc-2, respectively. PCR detection of BBTV in crude sap indicated that the freezing of banana tissue in liquid nitrogen (LN2) before extraction was more effective than using sand as the extraction technique. BBTV was also detected using PCR assay in 69 healthy and diseased plants using Na-PO4 buffer containing 1 % SDS. PCR detection of BBTV in nucleic acid extracts using seven different extraction buffers to adapt the use of PCR in routine detection in the field was studied. Results proved that BBTV was detected with high sensitivity in nucleic acid extracts more than in infectious sap. The results also suggested the common aetiology for the BBTV by the PCR reactions of BBTV in nucleic acid extracts from Australia, Burundi, Egypt, France, Gabon, Philippines and Taiwan. Results also proved a positive relation between the Egyptian-BBTV isolate and abaca bunchy top isolate from the Philippines, but there no relation was found with the Cucumber mosaic cucumovirus (CMV) isolates from Egypt and Philippines and Banana bract mosaic virus (BBMV) were found.
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Banana bunchy top disease (BBTD) caused by banana bunchy top virus (BBTV) was radioactively detected by nucleic acid hybridization techniques. Results showed that, 32P-labelled insert of pBT338 was hybridized with nucleic acid extracts from BBTV-infected plants from Egypt and Australia but not with those from CMV-infected plants from Egypt. Results revealed that BBTV was greatly detected in midrib, roots, meristem, corm, leaves and pseudostem respectively. BBTV was also detected in symptomless young plants prepared from diseased plant materials grown under tissue culture conditions but was not present in those performed from healthy plant materials. The sensitivity of dot blot and Southern blot hybridizations for the detection of BBTV was also performed for the detection of BBTV.
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Spoken word production is assumed to involve stages of processing in which activation spreads through layers of units comprising lexical-conceptual knowledge and their corresponding phonological word forms. Using high-field (4T) functional magnetic resonance imagine (fMRI), we assessed whether the relationship between these stages is strictly serial or involves cascaded-interactive processing, and whether central (decision/control) processing mechanisms are involved in lexical selection. Participants performed the competitor priming paradigm in which distractor words, named from a definition and semantically related to a subsequently presented target picture, slow picture-naming latency compared to that with unrelated words. The paradigm intersperses two trials between the definition and the picture to be named, temporally separating activation in the word perception and production networks. Priming semantic competitors of target picture names significantly increased activation in the left posterior temporal cortex, and to a lesser extent the left middle temporal cortex, consistent with the predictions of cascaded-interactive models of lexical access. In addition, extensive activation was detected in the anterior cingulate and pars orbitalis of the inferior frontal gyrus. The findings indicate that lexical selection during competitor priming is biased by top-down mechanisms to reverse associations between primed distractor words and target pictures to select words that meet the current goal of speech.
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Construction professional service (CPS) in the international arena has been very competitive despite that the industry is proliferating at a high rate. To excel in international business, CPS firms have the importance of building overseas competition strategies on a proper understanding of the international CPS (I-CPS) market. However, subject to borderless trade, information technology–based networking, global outsourcing, and changing forms of procurement, the I-CPS market structure has become more covert, intricate, and unstraightforward than before. Through examining business competition among top international design firms, this study aims to identify the attributes of the I-CPS market structure from two perspectives—concentration and turnover. Data from Engineering News-Record over the period 2001–2011 were collected to calculate market concentration ratios and turnover indices. The results show that I-CPS competition is characterized by atomism, much turbulence with a steady increase in competition intensity, and the predominant role of new entrants and exiting firms in market turnovers. The combination of concentration and turnover is found useful to address the attributes of the I-CPS market structure, which favors I-CPS firms to formulate international competition strategies in due ways.
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Bottom emitting organic light emitting diodes (OLEDs) can suffer from lower external quantum efficiencies (EQE) due to inefficient out-coupling of the generated light. Herein, it is demonstrated that the current efficiency and EQE of red, yellow, and blue fluorescent single layer polymer OLEDs is significantly enhanced when a MoOx(5 nm)/Ag(10 nm)/MoOx(40 nm) stack is used as the transparent anode in a top emitting OLED structure. A maximum current efficiency and EQE of 21.2 cd/A and 6.7%, respectively, was achieved for a yellow OLED, while a blue OLED achieved a maximum of 16.5 cd/A and 10.1%, respectively. The increase in light out-coupling from the top-emitting OLEDs led to increase in efficiency by a factor of up to 2.2 relative to the optimised bottom emitting devices, which is the best out-coupling reported using solution processed polymers in a simple architecture and a significant step forward for their use in large area lighting and displays.