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1.
Query processing over object views of relational data 总被引:2,自引:0,他引:2
Gustav Fahl Tore Risch 《The VLDB Journal The International Journal on Very Large Data Bases》1997,6(4):261-281
This paper presents an approach to object view management for relational databases. Such a view mechanism makes it possible for users to transparently work with data in
a relational database as if it was stored in an object-oriented (OO) database. A query against the object view is translated
to one or several queries against the relational database. The results of these queries are then processed to form an answer
to the initial query. The approach is not restricted to a ‘pure’ object view mechanism for the relational data, since the
object view can also store its own data and methods. Therefore it must be possible to process queries that combine local data
residing in the object view with data retrieved from the relational database. We discuss the key issues when object views
of relational databases are developed, namely: how to map relational structures to sub-type/supertype hierarchies in the view,
how to represent relational database access in OO query plans, how to provide the concept of object identity in the view,
how to handle the fact that the extension of types in the view depends on the state of the relational database, and how to
process and optimize queries against the object view. The results are based on experiences from a running prototype implementation.
Edited by: M.T. ?zsu. Received April 12, 1995 / Accepted April 22, 1996 相似文献
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Abstract. Providing a customized result set based upon a user preference is the ultimate objective of many content-based image retrieval
systems. There are two main challenges in meeting this objective: First, there is a gap between the physical characteristics
of digital images and the semantic meaning of the images. Secondly, different people may have different perceptions on the
same set of images. To address both these challenges, we propose a model, named Yoda, that conceptualizes content-based querying
as the task of soft classifying images into classes. These classes can overlap, and their members are different for different
users. The “soft” classification is hence performed for each and every image feature, including both physical and semantic
features. Subsequently, each image will be ranked based on the weighted aggregation of its classification memberships. The
weights are user-dependent, and hence different users would obtain different result sets for the same query. Yoda employs
a fuzzy-logic based aggregation function for ranking images. We show that, in addition to some performance benefits, fuzzy
aggregation is less sensitive to noise and can support disjunctive queries as compared to weighted-average aggregation used
by other content-based image retrieval systems. Finally, since Yoda heavily relies on user-dependent weights (i.e., user profiles)
for the aggregation task, we utilize the users' relevance feedback to improve the profiles using genetic algorithms (GA).
Our learning mechanism requires fewer user interactions, and results in a faster convergence to the user's preferences as
compared to other learning techniques.
Correspondence to: Y.-S. Chen (E-mail: yishinc@usc.edu)
This research has been funded in part by NSF grants EEC-9529152 (IMSC ERC) and IIS-0082826, NIH-NLM R01-LM07061, DARPA and
USAF under agreement nr. F30602-99-1-0524, and unrestricted cash gifts from NCR, Microsoft, and Okawa Foundation. 相似文献
4.
In this paper, we propose a multi-level abstraction mechanism for capturing the spatial and temporal semantics associated
with various objects in an input image or in a sequence of video frames. This abstraction can manifest itself effectively
in conceptualizing events and views in multimedia data as perceived by individual users. The objective is to provide an efficient
mechanism for handling content-based queries, with the minimum amount of processing performed on raw data during query evaluation.
We introduce a multi-level architecture for video data management at different levels of abstraction. The architecture facilitates
a multi-level indexing/searching mechanism. At the finest level of granularity, video data can be indexed based on mere appearance
of objects and faces. For management of information at higher levels of abstractions, an object-oriented paradigm is proposed
which is capable of supporting domain specific views. 相似文献
5.
We present an efficient and accurate method for retrieving images based on color similarity with a given query image or histogram.
The method matches the query against parts of the image using histogram intersection. Efficient searching for the best matching
subimage is done by pruning the set of subimages using upper bound estimates. The method is fast, has high precision and recall
and also allows queries based on the positions of one or more objects in the database image. Experimental results showing
the efficiency of the proposed search method, and high precision and recall of retrieval are presented.
Received: 20 January 1997 / Accepted: 5 January 1998 相似文献
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Query by video clip 总被引:15,自引:0,他引:15
Typical digital video search is based on queries involving a single shot. We generalize this problem by allowing queries
that involve a video clip (say, a 10-s video segment). We propose two schemes: (i) retrieval based on key frames follows the traditional approach of identifying shots, computing key frames from a video, and then extracting image features
around the key frames. For each key frame in the query, a similarity value (using color, texture, and motion) is obtained
with respect to the key frames in the database video. Consecutive key frames in the database video that are highly similar
to the query key frames are then used to generate the set of retrieved video clips. (ii) In retrieval using sub-sampled frames, we uniformly sub-sample the query clip as well as the database video. Retrieval is based on matching color and texture features
of the sub-sampled frames. Initial experiments on two video databases (basketball video with approximately 16,000 frames and
a CNN news video with approximately 20,000 frames) show promising results. Additional experiments using segments from one
basketball video as query and a different basketball video as the database show the effectiveness of feature representation
and matching schemes. 相似文献
8.
NeTra: A toolbox for navigating large image databases 总被引:17,自引:0,他引:17
We present here an implementation of NeTra, a prototype image retrieval system that uses color, texture, shape and spatial
location information in segmented image regions to search and retrieve similar regions from the database. A distinguishing
aspect of this system is its incorporation of a robust automated image segmentation algorithm that allows object- or region-based
search. Image segmentation significantly improves the quality of image retrieval when images contain multiple complex objects.
Images are segmented into homogeneous regions at the time of ingest into the database, and image attributes that represent
each of these regions are computed. In addition to image segmentation, other important components of the system include an
efficient color representation, and indexing of color, texture, and shape features for fast search and retrieval. This representation
allows the user to compose interesting queries such as “retrieve all images that contain regions that have the color of object
A, texture of object B, shape of object C, and lie in the upper of the image”, where the individual objects could be regions
belonging to different images. A Java-based web implementation of NeTra is available at http://vivaldi.ece.ucsb.edu/Netra. 相似文献
9.
Analyzing scenery images by monotonic tree 总被引:3,自引:0,他引:3
Content-based image retrieval (CBIR) has been an active research area in the last ten years, and a variety of techniques
have been developed. However, retrieving images on the basis of low-level features has proven unsatisfactory, and new techniques
are needed to support high-level queries. Research efforts are needed to bridge the gap between high-level semantics and low-level
features. In this paper, we present a novel approach to support semantics-based image retrieval. Our approach is based on
the monotonic tree, a derivation of the contour tree for use with discrete data. The structural elements of an image are modeled
as branches (or subtrees) of the monotonic tree. These structural elements are classified and clustered on the basis of such
properties as color, spatial location, harshness and shape. Each cluster corresponds to some semantic feature. This scheme
is applied to the analysis and retrieval of scenery images. Comparisons of experimental results of this approach with conventional
techniques using low-level features demonstrate the effectiveness of our approach. 相似文献
10.
A knowledge-based approach for retrieving images by content 总被引:10,自引:0,他引:10
Chih-Cheng Hsu Chu W.W. Taira R.K. 《Knowledge and Data Engineering, IEEE Transactions on》1996,8(4):522-532
A knowledge based approach is introduced for retrieving images by content. It supports the answering of conceptual image queries involving similar-to predicates, spatial semantic operators, and references to conceptual terms. Interested objects in the images are represented by contours segmented from images. Image content such as shapes and spatial relationships are derived from object contours according to domain specific image knowledge. A three layered model is proposed for integrating image representations, extracted image features, and image semantics. With such a model, images can be retrieved based on the features and content specified in the queries. The knowledge based query processing is based on a query relaxation technique. The image features are classified by an automatic clustering algorithm and represented by Type Abstraction Hierarchies (TAHs) for knowledge based query processing. Since the features selected for TAH generation are based on context and user profile, and the TAHs can be generated automatically by a clustering algorithm from the feature database, our proposed image retrieval approach is scalable and context sensitive. The performance of the proposed knowledge based query processing is also discussed 相似文献
11.
Approximate query processing using wavelets 总被引:7,自引:0,他引:7
Kaushik Chakrabarti Minos Garofalakis Rajeev Rastogi Kyuseok Shim 《The VLDB Journal The International Journal on Very Large Data Bases》2001,10(2-3):199-223
Approximate query processing has emerged as a cost-effective approach for dealing with the huge data volumes and stringent
response-time requirements of today's decision support systems (DSS). Most work in this area, however, has so far been limited
in its query processing scope, typically focusing on specific forms of aggregate queries. Furthermore, conventional approaches
based on sampling or histograms appear to be inherently limited when it comes to approximating the results of complex queries
over high-dimensional DSS data sets. In this paper, we propose the use of multi-dimensional wavelets as an effective tool
for general-purpose approximate query processing in modern, high-dimensional applications. Our approach is based on building
wavelet-coefficient synopses of the data and using these synopses to provide approximate answers to queries. We develop novel query processing algorithms
that operate directly on the wavelet-coefficient synopses of relational tables, allowing us to process arbitrarily complex
queries entirely in the wavelet-coefficient domain. This guarantees extremely fast response times since our approximate query execution engine
can do the bulk of its processing over compact sets of wavelet coefficients, essentially postponing the expansion into relational
tuples until the end-result of the query. We also propose a novel wavelet decomposition algorithm that can build these synopses
in an I/O-efficient manner. Finally, we conduct an extensive experimental study with synthetic as well as real-life data sets
to determine the effectiveness of our wavelet-based approach compared to sampling and histograms. Our results demonstrate
that our techniques: (1) provide approximate answers of better quality than either sampling or histograms; (2) offer query
execution-time speedups of more than two orders of magnitude; and (3) guarantee extremely fast synopsis construction times
that scale linearly with the size of the data.
Received: 7 August 2000 / Accepted: 1 April 2001 Published online: 7 June 2001 相似文献
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Despite the efforts to reduce the so-called semantic gap between the user's perception of image similarity and the feature-based representation of images, the interaction with the user remains fundamental to improve performances of content-based image retrieval systems. To this end, relevance feedback mechanisms are adopted to refine image-based queries by asking users to mark the set of images retrieved in a neighbourhood of the query as being relevant or not. In this paper, the Bayesian decision theory is used to estimate the boundary between relevant and non-relevant images. Then, a new query is computed whose neighbourhood is likely to fall in a region of the feature space containing relevant images. The performances of the proposed query shifting method have been compared with those of other relevance feedback mechanisms described in the literature. Reported results show the superiority of the proposed method. 相似文献
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Integrated spatial and feature image query 总被引:3,自引:0,他引:3
We present a new system for querying for images by regions and their spatial and feature attributes. The system enables the
user to find the images that contain arrangements of regions similar to those diagrammed in a query image. By indexing the
attributes of regions, such as sizes, locations and visual features, a wide variety of complex joint spatial and feature queries
are efficiently computed. In order to demonstrate the utility of the system, we develop a process for the extracting color
regions from photographic images. We demonstrate that integrated spatial and feature querying using color regions improves
image search capabilities over non-spatial content-based image retrieval methods. 相似文献
17.
This paper provides a formal specification for concept-based image retrieval using triples. To effectively manage a vast amount of images, we may need an image retrieval system capable of indexing and searching images based on the characteristics of their content. However, such a content-based image retrieval technique alone may not satisfy user queries if retrieved images turn out to be relevant only when they are conceptually related with the queries. In this paper, we develop an image retrieval mechanism to extract semantics of images based on triples. The semantics can be captured by deriving concepts from its constituent objects and spatial relationships between them. The concepts are basically composite objects formed from the aggregation of the constituents. In our mechanism, all the spatial relationships between objects including the concepts are uniformly represented by triples, which are used for indexing images as well as capturing their semantics. We also develop a query evaluation for supporting the concept-based image retrieval. ©1999 John Wiley & Sons, Inc. 相似文献
18.
One key component in providing effective image data management support is an expressive query language/interface. In this
paper, we describe the EXQUISI system that we have developed. A main contribution of EXQUISI is its ability to allow a user
to express subtle differences that may exist between images to be retrieved and other images that are similar. In particular,
it allows the user to incorporate ambiguities and imprecisions in specifying his/her query. Another important aspect of EXQUISI
is the provision of a reformulation language by which the user can ask “like this in what” queries, by specifying which parts
of a returned image the user wants to include and exclude. 相似文献
19.
The GMAP: a versatile tool for physical data independence 总被引:1,自引:0,他引:1
Odysseas G. Tsatalos Marvin H. Solomon Yannis E. Ioannidis 《The VLDB Journal The International Journal on Very Large Data Bases》1996,5(2):101-118
Physical data independence is touted as a central feature of modern
database systems. It allows users to frame queries in terms of the logical
structure of the data, letting a query processor automatically translate
them into optimal plans that access physical storage structures. Both
relational and object-oriented systems, however, force users to frame their
queries in terms of a logical schema that is directly tied to physical
structures. We present an approach that eliminates this dependence. All
storage structures are defined in a declarative language based on
relational algebra as functions of a logical schema. We present an
algorithm, integrated with a conventional query optimizer, that translates
queries over this logical schema into plans that access the storage
structures. We also show how to compile update requests into plans that
update all relevant storage structures consistently and optimally.
Finally, we report on experiments with a prototype implementation of our
approach that demonstrate how it allows storage structures to be tuned to
the expected or observed workload to achieve significantly better
performance than is possible with conventional techniques.
Edited by
Matthias Jarke, Jorge Bocca, Carlo Zaniolo. Received
September 15, 1994 / Accepted September 1, 1995 相似文献
20.
A complete temporal relational algebra 总被引:5,自引:0,他引:5
Debabrata Dey Terence M. Barron Veda C. Storey 《The VLDB Journal The International Journal on Very Large Data Bases》1996,5(3):167-180
Various temporal extensions to the relational
model have been proposed. All
of these, however, deviate significantly from the original relational model.
This paper presents a temporal extension of the relational algebra that
is not significantly different from the original relational model, yet is
at least as expressive as any of the previous approaches. This algebra
employs multidimensional tuple time-stamping to capture the complete
temporal behavior of data. The basic relational operations are redefined as
consistent extensions of the existing operations in a manner that preserves
the basic algebraic equivalences of the snapshot (i.e., conventional static)
algebra. A new operation, namely temporal projection,
is introduced.
The complete update semantics are formally specified and aggregate functions
are defined. The algebra is closed, and reduces to the snapshot algebra. It
is also shown to be at least as expressive as the calculus-based temporal
query language TQuel. In order to assess the algebra, it is evaluated using
a set of twenty-six criteria proposed in the literature, and compared to
existing temporal relational algebras. The proposed algebra appears to
satisfy more criteria than any other
existing algebra.
Edited by
Wesley Chu. Received February 1993 / Accepted April
1995 相似文献