[1]
Supervised Hashing with Pseudo Labels for Scalable Multimedia Retrieval
Poster Session 1
/
Song, Jingkuan
/
Gao, Lianli
/
Yan, Yan
/
Zhang, Dongxiang
/
Sebe, Nicu
Proceedings of the 2015 ACM International Conference on Multimedia
2015-10-26
p.827-830
© Copyright 2015 ACM
Summary: There is an increasing interest in using hash codes for efficient multimedia
retrieval and data storage. The hash functions are learned in such a way that
the hash codes can preserve essential properties of the original space or the
label information. Then the Hamming distance of the hash codes can approximate
the data similarity. Existing works have demonstrated the success of many
supervised hashing models. However, labeling data is time and labor consuming,
especially for scalable datasets. In order to utilize the supervised hashing
models to improve the discriminative power of hash codes, we propose a
Supervised Hashing with Pseudo Labels (SHPL) which uses the cluster centers of
the training data to generate pseudo labels, based on which the hash codes can
be generated using the criteria of supervised hashing. More specifically, we
utilize linear discriminant analysis (LDA) with trace ratio criterion as a
showcase for hash functions learning and during the optimization, we prove that
the pseudo labels and the hash codes can be jointly learned and iteratively
updated in an unified framework. The learned hash functions can harness the
discriminant power of trace ratio criterion, and thus can achieve better
performance. Experimental results on three large-scale unlabeled datasets
(i.e., SIFT1M, GIST1M, and SIFT1B) demonstrate the superior performance of our
SHPL over existing hashing methods.
[2]
Exploring Viewable Angle Information in Georeferenced Video Search
Poster Session 1
/
Hu, Gang
/
Shao, Jie
/
Gao, Lianli
/
Yang, Yang
Proceedings of the 2015 ACM International Conference on Multimedia
2015-10-26
p.839-842
© Copyright 2015 ACM
Summary: As positioning data and other sensor information such as orientation
measurement became powerful contextual features generated by mobile devices
during video recording, a model capturing geographic field-of-view (FOV) has
been developed for georeferenced video search. The accurate representation of
an FOV is through the geometric shape of a circular sector. However, previous
work simply employed a rectilinear vector model to represent the coverage area
of a video scene. In this study, we propose to use a novel circular sector
model with beginning-ending vectors for FOV representation which additionally
explores viewable angle information. Its major advantage is that it leads to a
more accurate georeferenced video search without false positives or false
negatives (which occur in previous model using single vector). We demonstrate
how our model can be applied to perform different types of overlap queries for
spatial data selection in a unified framework, while providing competitive
performance in terms of efficiency.
[3]
Scalable Multimedia Retrieval by Deep Learning Hashing with Relative
Similarity Learning
Poster Session 1
/
Gao, Lianli
/
Song, Jingkuan
/
Zou, Fuhao
/
Zhang, Dongxiang
/
Shao, Jie
Proceedings of the 2015 ACM International Conference on Multimedia
2015-10-26
p.903-906
© Copyright 2015 ACM
Summary: Learning-based hashing methods are becoming the mainstream for approximate
scalable multimedia retrieval. They consist of two main components: hash codes
learning for training data and hash functions learning for new data points.
Tremendous efforts have been devoted to designing novel methods for these two
components, i.e., supervised and unsupervised methods for learning hash codes,
and different models for inferring hashing functions. However, there is little
work integrating supervised and unsupervised hash codes learning into a single
framework. Moreover, the hash function learning component is usually based on
hand-crafted visual features extracted from the training images. The
performance of a content-based image retrieval system crucially depends on the
feature representation and such hand-crafted visual features may degrade the
accuracy of the hash functions. In this paper, we propose a semi-supervised
deep learning hashing (DLH) method for fast multimedia retrieval. More
specifically, in the first component, we utilize both visual and label
information to learn an relative similarity graph that can more precisely
reflect the relationship among training data, and then generate the hash codes
based on the graph. In the second stage, we apply a deep convolutional neural
network (CNN) to simultaneously learn a good multimedia representation and hash
functions. Extensive experiments on three popular datasets demonstrate the
superiority of our DLH over both supervised and unsupervised hashing methods.
[4]
Chronological Citation Recommendation with Information-Need Shifting
Session 6E: Citation Networks
/
Jiang, Zhuoren
/
Liu, Xiaozhong
/
Gao, Liangcai
Proceedings of the 2015 ACM Conference on Information and Knowledge
Management
2015-10-19
p.1291-1300
© Copyright 2015 ACM
Summary: As the volume of publications has increased dramatically, an urgent need has
developed to assist researchers in locating high-quality, candidate-cited
papers from a research repository. Traditional scholarly-recommendation
approaches ignore the chronological nature of citation recommendations. In this
study, we propose a novel method called "Chronological Citation Recommendation"
which assumes initial user information needs could shift while users are
searching for papers in different time slices. We model the information-need
shifts with two-level modeling: dynamic time-related ranking feature
construction and dynamic evolving feature weight training. In more detail, we
employed a supervised document influence model to characterize the content
"time-varying" dynamics and constructed a novel heterogeneous graph that
encapsulates dynamic topic-based information, time-decay paper/topic citation
information, and word-based information. We applied multiple meta-paths for
different ranking hypotheses which carried different types of information for
citation recommendation in various time slices, along with information-need
shifting. We also used multiple learning-to-rank models to optimize the feature
weights for different time slices to generate the final "Chronological Citation
Recommendation" rankings. The use of Chronological Citation Recommendation
suggests time-series ranking lists based on initial user textual information
need and characterizes the information-need shifting. Experiments on the ACM
corpus show that Chronological Citation Recommendation can significantly
enhance citation recommendation performance.
[5]
Scientific Information Understanding via Open Educational Resources (OER)
Session 8B: Citations
/
Liu, Xiaozhong
/
Jiang, Zhuoren
/
Gao, Liangcai
Proceedings of the 2015 Annual International ACM SIGIR Conference on
Research and Development in Information Retrieval
2015-08-09
p.645-654
© Copyright 2015 ACM
Summary: Scientific publication retrieval/recommendation has been investigated in the
past decade. However, to the best of our knowledge, few efforts have been made
to help junior scholars and graduate students to understand and consume the
essence of those scientific readings. This paper proposes a novel
learning/reading environment, OER-based Collaborative PDF Reader (OCPR), that
incorporates innovative scaffolding methods that can: 1. auto-characterize
student emerging information need while reading a paper; and 2. enable students
to readily access open educational resources (OER) based on their information
need. By using metasearch methods, we pre-indexed 1,112,718 OERs, including
presentation videos, slides, algorithm source code, or Wikipedia pages, for
41,378 STEM publications. Based on the computational information need, we use
text mining and heterogeneous graph mining algorithms to recommend high quality
OERs to help students better understand the scientific content in the paper.
Evaluation results and exit surveys for an information retrieval course show
that the OCPR system alone with the recommended OERs can effectively assist
graduate students better understand the complex STEM publications. For
instance, 78.42% of participants believe the OCPR system and recommended OERs
can provide precise and useful information they need, while 78.43% of them
believe the recommended OERs are close to exactly what they need when reading
the paper. From OER ranking viewpoint, MRR, MAP and NDCG results prove that
learning to rank and cold start solutions can efficiently integrate different
text and graph ranking features.
[6]
WikiMirs 3.0: A Hybrid MIR System Based on the Context, Structure and
Importance of Formulae in a Document
Session 7 -- Non-text Collections
/
Wang, Yuehan
/
Gao, Liangcai
/
Wang, Simeng
/
Tang, Zhi
/
Liu, Xiaozhong
/
Yuan, Ke
JCDL'15: Proceedings of the 2015 ACM/IEEE-CS Joint Conference on Digital
Libraries
2015-06-21
p.173-182
© Copyright 2015 ACM
Summary: Nowadays, mathematical information is increasingly available in websites and
repositories, such like ArXiv, Wikipedia and growing numbers of digital
libraries. Mathematical formulae are highly structured and usually presented in
layout presentations, such as PDF, LATEX and Presentation MathML. The
differences of presentation between text and formulae challenge traditional
text-based index and retrieval methods. To address the challenge, this paper
proposes an upgraded Mathematical Information Retrieval (MIR) system, namely
WikiMirs 3.0, based on the context, structure and importance of formulae in a
document. In WikiMirs 3.0, users can easily "cut" formulae and contexts from
PDF documents as well as type in queries. Furthermore, a novel hybrid indexing
and matching model is proposed to support both exact and fuzzy matching. In the
hybrid model, both context and structure information of formulae are taken into
consideration. In addition, the concept of formula importance within a document
is introduced into the model for more reasonable ranking. Experimental results,
compared with two classical MIR systems, demonstrate that the proposed system
along with the novel model provides higher accuracy and better ranking results
over Wikipedia.
[7]
Querying Web-Scale Information Networks Through Bounding Matching Scores
Technical Papers
/
Jin, Jiahui
/
Khemmarat, Samamon
/
Gao, Lixin
/
Luo, Junzhou
Proceedings of the 2015 International Conference on the World Wide Web
2015-05-18
v.1
p.527-537
© Copyright 2015 ACM
Summary: Web-scale information networks containing billions of entities are common
nowadays. Querying these networks can be modeled as a subgraph matching
problem. Since information networks are incomplete and noisy in nature, it is
important to discover answers that match exactly as well as answers that are
similar to queries. Existing graph matching algorithms usually use graph
indices to improve the efficiency of query processing. For web-scale
information networks, it may not be feasible to build the graph indices due to
the amount of work and the memory/storage required. In this paper, we propose
an efficient algorithm for finding the best k answers for a given query without
precomputing graph indices. The quality of an answer is measured by a matching
score that is computed online. To speed up query processing, we propose a novel
technique for bounding the matching scores during the computation. By using
bounds, we can efficiently prune the answers that have low qualities without
having to evaluate all possible answers. The bounding technique can be
implemented in a distributed environment, allowing our approach to efficiently
answer the queries on web-scale information networks. We demonstrate the
effectiveness and the efficiency of our approach through a series of
experiments on real-world information networks. The result shows that our
bounding technique can reduce the running time up to two orders of magnitude
comparing to an approach that does not use bounds.
[8]
Scalable Distributed Belief Propagation with Prioritized Block Updates
KM Session 15: Knowledge Representation & Reasoning II
/
Yin, Jiangtao
/
Gao, Lixin
Proceedings of the 2014 ACM Conference on Information and Knowledge
Management
2014-11-03
p.1209-1218
© Copyright 2014 ACM
Summary: Belief propagation (BP) is a popular method for performing approximate
inference on probabilistic graphical models. However, its message updates are
time-consuming, and the schedule for updating messages is crucial to its
running time and even convergence. In this paper, we propose a new scheduling
scheme that selects a set of messages to update at a time and leverages a novel
priority to determine which messages are selected. Additionally, an incremental
update approach is introduced to accelerate the computation of the priority. As
the size of the model grows, it is desirable to leverage the parallelism of a
cluster of machines to reduce the inference time. Therefore, we design a
distributed framework, Prom, to facilitate the implementation of BP algorithms.
We evaluate the proposed scheduling scheme (supported by Prom) via extensive
experiments on a local cluster as well as the Amazon EC2 cloud. The evaluation
results show that our scheduling scheme outperforms the state-of-the-art
counterpart.
[9]
Comic2CEBX: A system for automatic comic content adaptation
Data transformation and description
/
Li, Luyuan
/
Wang, Yongtao
/
Gao, Liangcai
/
Tang, Zhi
/
Suen, Ching Y.
JCDL'14: Proceedings of the 2014 ACM/IEEE-CS Joint Conference on Digital
Libraries
2014-09-08
p.299-308
Keywords: Feature extraction
Keywords: Image edge detection
Keywords: Image segmentation
Keywords: Layout
Keywords: Nonhomogeneous media
Keywords: Pattern recognition
Keywords: Visualization
Keywords: CEBX Document Standard
Keywords: Comic Image
Keywords: Conditional Random Fields
Keywords: Content Reflow and Adaptation
Keywords: Page Layout Analysis
Keywords: Panel Detection
© Copyright 2014 IEEE
Summary: Comics are popular almost throughout the world. With the help of comic
document digitization, it is much easier for people to archive and browse comic
works. However, there are still some big challenges along with comic document
digitization progress. Among these challenges, comic content adaptation is an
important one to be tackled. The existing works only focus on parts of this
problem and do not provide a tangible solution to display comic contents on
different devices. In this paper, we solve these problems by proposing
Comic2CEBX, a system which can automatically convert a set of scanned comic
page images into a CEBX file that allows reflowing of the original comic pages
with fixed layouts. Taking raw comic images as inputs, our system first
extracts three kinds of low-level visual patterns and then uses multilayer
Conditional Random Fields to detect all the panels. Meanwhile, our system
automatically identifies the reading orders of the panels within each page.
Finally, we encapsulate the comic page images and the obtained page structure
information (i.e., the panels detection results and the corresponding reading
orders) to generate a CEBX file. Experimental results show that our comic page
layout analysis method achieves better performance than the existing ones, and
use case presentation of the CEBX files produced by our system demonstrates
that it brings better comic reading experience especially on mobile devices.
[10]
Full-text based context-rich heterogeneous network mining approach for
citation recommendation
Citation, citation, citation
/
Liu, Xiaozhong
/
Yu, Yingying
/
Guo, Chun
/
Sun, Yizhou
/
Gao, Liangcai
JCDL'14: Proceedings of the 2014 ACM/IEEE-CS Joint Conference on Digital
Libraries
2014-09-08
p.361-370
Keywords: Abstracts
Keywords: Citation analysis
Keywords: Context
Keywords: Data mining
Keywords: Educational institutions
Keywords: Focusing
Keywords: Inference algorithms
Keywords: Citation Recommendation
Keywords: Full-text Citation Analysis
Keywords: Heterogeneous Information Network
Keywords: Meta-Path
© Copyright 2014 IEEE
Summary: Citation relationship between scientific publications has been successfully
used for scholarly bibliometrics, information retrieval and data mining tasks,
and citation-based recommendation algorithms are well documented. While
previous studies investigated citation relations from various viewpoints, most
of them share the same assumption that, if paper1 cites paper2 (or author1
cites author2), they are connected, regardless of citation importance,
sentiment, reason, topic, or motivation. However, this assumption is
oversimplified. In this study, we employ an innovative "context-rich
heterogeneous network" approach, which paves a new way for citation
recommendation task. In the network, we characterize 1) the importance of
citation relationships between citing and cited papers, and 2) the topical
citation motivation. Unlike earlier studies, the citation information, in this
paper, is characterized by citation textual contexts extracted from the
full-text citing paper. We also propose algorithm to cope with the situation
when large portion of full-text missing information exists in the bibliographic
repository. Evaluation results show that, context-rich heterogeneous network
can significantly enhance the citation recommendation performance.
[11]
A mathematics retrieval system for formulae in layout presentations
Session 7c: signs and symbols
/
Lin, Xiaoyan
/
Gao, Liangcai
/
Hu, Xuan
/
Tang, Zhi
/
Xiao, Yingnan
/
Liu, Xiaozhong
Proceedings of the 2014 Annual International ACM SIGIR Conference on
Research and Development in Information Retrieval
2014-07-06
p.697-706
© Copyright 2014 ACM
Summary: The semantics of mathematical formulae depend on their spatial structure,
and they usually exist in layout presentations such as PDF, LaTeX, and
Presentation MathML, which challenges previous text index and retrieval
methods. This paper proposes an innovative mathematics retrieval system along
with the novel algorithms, which enables efficient formula index and retrieval
from both webpages and PDF documents. Unlike prior studies, which require users
to manually input formula markup language as query, the new system enables
users to "copy" formula queries directly from PDF documents. Furthermore, by
using a novel indexing and matching model, the system is aimed at searching for
similar mathematical formulae based on both textual and spatial similarities. A
hierarchical generalization technique is proposed to generate sub-trees from
the semi-operator tree of formulae and support substructure match and fuzzy
match. Experiments based on massive Wikipedia and CiteSeer repositories show
that the new system along with novel algorithms, comparing with two
representative mathematics retrieval systems, provides more efficient
mathematical formula index and retrieval, while simplifying user query input
for PDF documents.
[12]
A Study of Kinect-Based Smart TV Control Mode
Cross-Cultural Issues in Interaction
/
Li, He
/
Qiu, Jing
/
Gao, Long
CCD 2014: 6th International Conference on Cross-Cultural Design
2014-06-22
p.174-183
Keywords: Kinect; Gesture Control; Smart TV Control Mode
© Copyright 2014 Springer International Publishing
Summary: TV plays a more and more important role in daily life. And it will be a
protagonist in our home. However, the progress of smart TV control mode did not
catch up with the development of smart TV's software and hardware. In this
paper, a survey was conducted to confirm the way of future smart TV control
mode. According to the results of the survey, an experiment was executed in
order to investigate design parameters of the new smart TV control mode.
Therefore, the precautions on design the smart TV control mode was proposed.
[13]
Road traffic prediction by incorporating online information
Connecting online & offline life workshop (COOL 2014)
/
Zhou, Tian
/
Gao, Lixin
/
Ni, Daiheng
Companion Proceedings of the 2014 International Conference on the World Wide
Web
2014-04-07
v.2
p.1235-1240
© Copyright 2014 ACM
Summary: Road traffic conditions are typically affected by events such as extreme
weather or sport games. With the advance of Web, events and weather conditions
can be readily retrieved in real-time. In this paper, we propose a traffic
condition prediction system incorporating both online and offline information.
RFID-based system has been deployed for monitoring road traffic. By
incorporating data from both road traffic monitoring system and online
information, we propose a hierarchical Bayesian network to predict road traffic
condition. Using historical data, we establish a hierarchical Bayesian network
to characterize the relationships among events and road traffic conditions. To
evaluate the model, we use the traffic data collected in Western Massachusetts
as well as online information about events and weather. Our proposed prediction
achieves an accuracy of 93% overall.
[14]
WikiMirs: a mathematical information retrieval system for wikipedia
Web 2.0
/
Hu, Xuan
/
Gao, Liangcai
/
Lin, Xiaoyan
/
Tang, Zhi
/
Lin, Xiaofan
/
Baker, Josef B.
JCDL'13: Proceedings of the 2013 ACM/IEEE-CS Joint Conference on Digital
Libraries
2013-07-22
p.11-20
© Copyright 2013 ACM
Summary: Mathematical formulae in structural formats such as MathML and LaTeX are
becoming increasingly available. Moreover, repositories and websites, including
ArXiv and Wikipedia, and growing numbers of digital libraries use these
structural formats to present mathematical formulae. This presents an important
new and challenging area of research, namely Mathematical Information Retrieval
(MIR). In this paper, we propose WikiMirs, a tool to facilitate mathematical
formula retrieval in Wikipedia. WikiMirs is aimed at searching for similar
mathematical formulae based upon both textual and spatial similarities, using a
new indexing and matching model developed for layout structures. A hierarchical
generalization technique is proposed to generate sub-trees from presentation
trees of mathematical formulae, and similarity is calculated based upon
matching at different levels of these trees. Experimental results show that
WikiMirs can efficiently support sub-structure matching and similarity matching
of mathematical formulae. Moreover, WikiMirs obtains both higher accuracy and
better ranked results over Wikipedia in comparison to Wikipedia Search and
Egomath. We conclude that WikiMirs provides a new, alternative, and hopefully
better service for users to search mathematical expressions within Wikipedia.
[15]
Webpage Designs for Diverse Cultures: An Exploratory Study of User
Preferences in China
Cross-Cultural, Intercultural and Social Issues
/
Su, Yin
/
Liu, David
/
Yuan, Xiaomeng
/
Ting, Justin
/
Jiang, Jingguo
/
Wang, Li
/
Gao, Lin
Proceedings of IFIP INTERACT'13: Human-Computer Interaction-1
2013
v.1
p.339-346
Keywords: webpage design; cross-culture; diversity; Chinese users
© Copyright 2013 IFIP
Summary: A wealth of studies has revealed a cross-cultural difference in the user
preference on webpage designs. Users from other cultures often criticize a
widely accepted webpage design in one culture. Designs for diverse cultures are
thus expected to be specific to address diverse user preferences. This study
investigated the preferences of Chinese users on four essential design elements
related to the readability of texts of the result pages of search engines. The
results suggested that the search result pages of the Bing search engine
designed for typical 'US users' did not satisfy Chinese users. Chinese users,
in general, preferred huge-sized texts for titles, a more compact layout of the
search result pages, and keywords to be highlighted in red. The findings of the
study contributed to webpage design guidelines for Chinese users, and may serve
as a catalyst in exploring user preferences in designing for diverse cultures.
[16]
Web-based citation parsing, correction and augmentation
Citations
/
Gao, Liangcai
/
Qi, Xixi
/
Tang, Zhi
/
Lin, Xiaofan
/
Liu, Ying
JCDL'12: Proceedings of the 2012 Joint International Conference on Digital
Libraries
2012-06-10
p.295-304
© Copyright 2012 ACM
Summary: Considering the tremendous value of citation metadata, many methods have
been proposed to automate Citation Metadata Extraction (CME). The existing
methods primarily rely on the content analysis of citation text. However, the
results from such content-based methods are often unreliable. Moreover, the
extracted citation metadata is only a small part of the relevant metadata that
spreads across the Internet. As opposed to the content-based CME methods, this
paper proposes a Web-based CME approach and a citation enriching system, called
as BibAll, which is capable of correcting the parsing results of content-based
CME methods and augmenting citation metadata by leveraging relevant
bibliographic data from digital repositories and cited-by publications on the
Web. BibAll consists of four main components: citation parsing, Web-based
bibliographic data retrieval, irrelevant bibliographic data filtering, and
relevant bibliographic data integration. The system has been tested on the
publicly available FLUX-CIM dataset. Experimental results show that BibAll
significantly improves the citation parsing accuracy and augments the metadata
of the original citation.
[17]
Adaboost with SVM-Based Classifier for the Classification of Brain Motor
Imagery Tasks
Eye Tracking, Gestures and Brain Interfaces
/
Wang, Jue
/
Gao, Lin
/
Zhang, Haoshi
/
Xu, Jin
UAHCI 2011: 6th International Conference on Universal Access in
Human-Computer Interaction, Part II: Users Diversity
2011-07-09
v.2
p.629-634
Keywords: Adaboost; SVM; Classification; Kolmogorov entropy; ERS/ERD; Motor imagery
Copyright © 2011 Springer-Verlag
Summary: The Adaboost with SVM-based component classifier is generally considered to
break the Boosting principle for the difficulty in training of SVM and have
imbalance between the diversity and accuracy over basic SVM classifiers. The
Adaboost classifier in the paper trains SVM as base classifier with changing
kernel function parameter σ value, which progressively reduces with the
changes of weight value of training sample. To testify the validity of the
classifier, the classifier is tested on human subjects to classify the left-
and right-hand motor imagery tasks. The average classification accuracy reaches
90.2% on test data, which greatly outperforms SVM classifiers without Adaboost
and commonly Fisher Linear Discriminant classifier. The results confirm that
the proposed combination of Adaboost with SVM classifier may improve accuracy
for classification of motor imagery tasks, and have applications to performance
improvement of brain-computer interface (BCI) systems.
[18]
Structure extraction from PDF-based book documents
Automated methods to help our understanding of texts
/
Gao, Liangcai
/
Tang, Zhi
/
Lin, Xiaofan
/
Liu, Ying
/
Qiu, Ruiheng
/
Wang, Yongtao
JCDL'11: Proceedings of the 2011 Joint International Conference on Digital
Libraries
2011-06-13
p.11-20
© Copyright 2011 ACM
Summary: Nowadays PDF documents have become a dominating knowledge repository for
both the academia and industry largely because they are very convenient to
print and exchange. However, the methods of automated structure information
extraction are yet to be fully explored and the lack of effective methods
hinders the information reuse of the PDF documents. To enhance the usability
for PDF-formatted electronic books, we propose a novel computational framework
to analyze the underlying physical structure and logical structure. The
analysis is conducted at both page level and document level, including global
typographies, reading order, logical elements, chapter/section hierarchy and
metadata. Moreover, two characteristics of PDF-based books, i.e., style
consistency in the whole book document and natural rendering order of PDF
files, are fully exploited in this paper to improve the conventional
image-based structure extraction methods. This paper employs the bipartite
graph as a common structure for modeling various tasks, including reading order
recovery, figure and caption association, and metadata extraction. Based on the
graph representation, the optimal matching (OM) method is utilized to find the
global optima in those tasks. Extensive benchmarking using real-world data
validates the high efficiency and discrimination ability of the proposed
method.
[19]
CEBBIP: a parser of bibliographic information in chinese electronic books
Session 2
/
Gao, Liangcai
/
Tang, Zhi
/
Lin, Xiaofan
JCDL'09: Proceedings of the 2009 Joint International Conference on Digital
Libraries
2009-06-15
p.73-76
Keywords: bibliography, chinese electronic book, digital library, machine learning,
metadata extraction
© Copyright 2009 ACM
Summary: Bibliographic information is essential for many digital library
applications, such as citation analysis, academic searching and topic
discovery. And bibliographic data extraction has attracted a great deal of
attention in recent years. In this paper, we address the problem of automatic
extraction of bibliographic data in Chinese electronic book and propose a tool
called CEBBIP* for the task, which includes three main systems: data
preprocessing, data parsing and data postprocessing. In the data preprocessing
system, the tool adopts a rules-based method to locate citation data in a book
and to segment citation data into citation strings of individual referencing
literature. And a learning-based approach, Conditional Random Fields (CRF), is
employed to parse citation strings in the data parsing system. Finally, the
tool takes advantage of document intrinsic local format consistency to enhance
citation data segmentation and parsing through clustering techniques. CEBBIP
has been used in a commercial E-book production system. Experimental results
show that CEBBIP's precision rate is very high. More specially, adopting the
document intrinsic local format consistency obviously improves the citation
data segmenting and parsing accuracy.
[20]
XEB: a markup language document container format suitable for handheld
devices
Demos
/
Tang, Zhi
/
Gao, Liangcai
/
Jia, Aixia
/
Lin, Xiaofan
JCDL'09: Proceedings of the 2009 Joint International Conference on Digital
Libraries
2009-06-15
p.481-482
Keywords: document parsing, handheld device, markup language document
© Copyright 2009 ACM
Summary: We propose a new document container format (XEB, eXtensible Electronic Book)
based on block mechanism to efficiently process markup language documents in
handheld devices. And random document access is also supported in the format
through a pagination mechanism. The format has already been applied to a number
of handheld devices' Chinese E-book readers and XEB documents can be downloaded
from a Chinese E-book store.
[21]
A Motion Compensated De-interlacing Algorithm for Motive Object Capture
Part I: Shape and Movement Modeling and Anthropometry
/
Gao, Lei
/
Li, Chao
/
Zhu, Chengjun
/
Xiong, Zhang
DHM 2007: 1st International Conference on Digital Human Modeling
2007-07-22
p.74-81
Keywords: de-interlacing; motion compensation; motion estimation; motion detect;
motion object
Copyright © 2007 Springer-Verlag
Summary: A motion compensated de-interlacing algorithm is proposed to recover the
defects of interlaced video frame for capturing motion object. In this
algorithm, two anti-noise background fields are formed by analyzing the
temporal correlation of pixels between adjacent same parity fields. To each
field, the subtraction with the corresponding background is used to detect
motion object. To avoid the inaccurate detection caused by the difference
between the spatial scanning positions of odd and even field, the motion
objects are detected with same parity field and background field. Then motion
estimation technology is used to measures the inter-field motion, find out the
motion vector between the odd field and even field. Based on the motion vector,
an interpolation filter is designed to shift the pixels of the motion object in
the two temporally displaced fields to a common point in time. This
de-interlacing algorithm maximizes the vertical resolution of the motion
objects. Experimental results show that the proposed algorithm could achieve
higher image quality on motion object, and the computational complexity is
acceptable for consumer computer applications.
[22]
Application specific data replication for edge services
Consistency and replication
/
Gao, Lei
/
Dahlin, Mike
/
Nayate, Amol
/
Zheng, Jiandan
/
Iyengar, Arun
Proceedings of the 2003 International Conference on the World Wide Web
2003-05-20
p.449-460
Keywords: availability, data replication, distributed objects, edge services,
performance, wide area networks (WAN)
© Copyright 2003 Authors
Summary: The emerging edge services architecture promises to improve the availability
and performance of web services by replicating servers at geographically
distributed sites. A key challenge in such systems is data replication and
consistency so that edge server code can manipulate shared data without
incurring the availability and performance penalties that would be incurred by
accessing a traditional centralized database. This paper explores using a
distributed object architecture to build an edge service system for an
e-commerce application, an online bookstore represented by the TPC-W benchmark.
We take advantage of application specific semantics to design distributed
objects to manage a specific subset of shared information using simple and
effective consistency models. Our experimental results show that by slightly
relaxing consistency within individual distributed objects, we can build an
edge service system that is highly available and efficient. For example, in one
experiment we find that our object-based edge server system provides a factor
of five improvement in response time over a traditional centralized cluster
architecture and a factor of nine improvement over an edge service system that
distributes code but retains a centralized database.
[23]
Resource management for scalable disconnected access to Web services
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Chandra, Bharat
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Dahlin, Mike
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Gao, Lei
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Khoja, Amjad-Ali
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Nayate, Amol
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Razzaq, Asim
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Sewani, Anil
Proceedings of the 2001 International Conference on the World Wide Web
2001-05-01
p.245-256
© Copyright 2001 Authors
