An Information Storage System for Large-Scale Knowledge Resources

Transcription

1 An Information Storage System for Large-Scale Knowledge Resources Haruo Yokota Global Scientific Information and Computing Center Tokyo Institute of Technology

2 Outline The goal and requirements of an information storage system for this project Our approach to realize the goal Examples of services using the system Software and hardware configurations of the system Concluding remarks March 9, 2004 Haruo Yokota (GSIC, Titech) 2

3 Goal Our Mission: Provide an infrastructure to support for interdisciplinary research In the Tokyo Institute of Technology 21st Century COE Program of Framework for Systematization and Application of Largescale Knowledge Resources Develop an advanced information storage system To preserve and utilize the large-scale knowledge resources for researchers and students March 9, 2004 Haruo Yokota (GSIC, Titech) 3

4 Flexibility and Extensibility These are key issues to implement the system The usages of the stored knowledge resources are assumed to have wide variety The configurations and functions of the system should be flexible The number of knowledge resources and access requests are expected to increase rapidly The system should be extensible March 9, 2004 Haruo Yokota (GSIC, Titech) 4

5 Information Component Examples Written texts & drawn figures Frequently combined in documents Data formats: flat text, postscript, pdf, ppt, etc. Printed materials e.g. pictures, scanned historical documents (the tale of Genji) Data format: bitmap data, jpeg, gif, etc. Recorded video streams & spontaneous speech To support e-learning and speech recognition research Data formats: mpeg, RealMedia, WindowsMedia, QuickTime, etc. Structured information e.g. corpus, experimental data, etc. Data formats: tables (relational databases), XML, etc. We may soon have other data formats and even other media (e.g. 3D contents) March 9, 2004 Haruo Yokota (GSIC, Titech) 5

6 Targets To Be Stored Printed Materials Drawn Figures Video Streams Written Texts Speeches Wide Variety Many Data Formats A Storage System Should be Flexible and Knowledge Resources Extensible March 9, 2004 Haruo Yokota (GSIC, Titech) 6

7 Approach To treat these wide and dynamic variety of information components, we take an approach to combine two types of systems: An advanced information storage system: KnowledgeStore (KS) Providing common functions for handling the variety of data formats External systems Dedicated for special applications based on the knowledge resources March 9, 2004 Haruo Yokota (GSIC, Titech) 7

8 External Systems Responsible for executing independent applications Using the information components preserved in the KnowledgeStore. The dynamics of environments Change of user requirements Appearance of new type of materials can easily be coped with by modifying some external systems locally or adding new one March 9, 2004 Haruo Yokota (GSIC, Titech) 8

9 KnowledgeStore (KS) Prepares web-service APIs to the external systems As well as ordinary web interfaces for interactive users The Web service is standardized interface between software components using HTTP and SOAP Provides common functions for these external application systems via the webservice APIs. March 9, 2004 Haruo Yokota (GSIC, Titech) 9

10 External System Interface External System 1 External System 2 External System n HTTP & SOAP KnowledgeStore Web Service APIs Common Functions Knowledge Resources March 9, 2004 Haruo Yokota (GSIC, Titech) 10

11 Common Functions Three Types of Functions: Contents Management Functions Contents Retrieval Functions Access Management Functions To implement them, we prepare Hierarchical collections as folders With user access authorization Metadata for each contents By referring Dublin Core (a metadata standard) March 9, 2004 Haruo Yokota (GSIC, Titech) 11

12 Contents Management User define Metadata Data Types Based on system predefined basic data type Integer, Floating Point Number, Date, Character Sting, File, XML, RDB, Video Stream, URL, Reference, etc. Contents Attributes Title, Creator, Subject, Description, Created Date, Modified Date, Language, Versions, etc. Contents Definition Collections of contents attributes March 9, 2004 Haruo Yokota (GSIC, Titech) 12

13 Contents Retrieval Search functions for the metadata Search targets can be specified by the data types and contents attributes Full text search functions for text contents Structural search functions for the RDB and XML contents Combinations of these functions in a folder or across multiple folders March 9, 2004 Haruo Yokota (GSIC, Titech) 13

14 Access Management There are a number of services having own user authorization mechanism If they requires password every time enter some service, it should be a trouble for users To avoid it, we adopt single sign-on (SSO) mechanisms for the services Provides user group management Administrators, External System Developers, Contents Register, General Users, etc. Preserves access logs March 9, 2004 Haruo Yokota (GSIC, Titech) 14

15 Overview of KS Users External System 1 External System n Single Sign-On Web Interface Web Service Interface Contents Retrieval Web Interface Web Service Interface Contents Management Web Interface Web Service Interface Access Management Contents Metadata Advanced Information Storage System: KnowledgeStore March 9, 2004 Haruo Yokota (GSIC, Titech) 15

16 Contents Management I/F Access Authorization is specified for each hierarchical folder March 9, 2004 Haruo Yokota (GSIC, Titech) 16

17 Contents Creation I/F Metadata can be specified for each content March 9, 2004 Haruo Yokota (GSIC, Titech) 17

18 Attribute Search Interface Contents can be searched with contents attributes March 9, 2004 Haruo Yokota (GSIC, Titech) 18

19 Examples of External Systems UPRISE (by Our Group) A presentation scene retrieval system Asunaro (by Group of Prof. Nishina) An e-learning system to study Japanese PRESRI (by Group of Prof. Okumura) A citation index collecting research papers from the WWW Research Mining (by Our Group) A system discovering macro-flows of research by applying a mining method to databases of papers And so on March 9, 2004 Haruo Yokota (GSIC, Titech) 19

20 UPRISE UPRISE:Unified Presentation slide Retrieval by Impression Search Engine It stores the combination of presentation slides and videos recording of the circumstances of the presentation To support retrieval services based on the impression indicators Expressing how well a slide matches the given keywords March 9, 2004 Haruo Yokota (GSIC, Titech) 20

21 Impression Indicators Consider properties of presentation slides Position Impression Indicator: I p Utilize structures of a presentation slide Duration Impression Indicator: I d Utilize the time information to select slides especially in the case of multiple appearances of the same slide by backtracking or reuse Context Impression Indicator: I c Utilize the context of a slide appearance sequence March 9, 2004 Haruo Yokota (GSIC, Titech) 21

22 Evaluation of the Indicators Extracting emergence of the relevant slide from multiple appearances of the same slide caused by the backtracking or reuse Asked ten testers to specify a target appearance for keywords they choose To determine the relevant emergence within multiple appearances in videos Each tester does six or seven experiments using different sets of keywords Use 20 presentations containing 849 slides and keywords March 9, 2004 Haruo Yokota (GSIC, Titech) 22

23 Comparison with tf.idf R anking by tf.idf Ranking by UPRISE Graph compares the ranking of the slide appearances specified by the testers. X: impression indicator Y: traditional tf.idf A point upper the diagonal line indicates the specified appearance is ranked higher in the list by the impression indicator; the inferiority for lower points. March 9, 2004 Haruo Yokota (GSIC, Titech) 23

24 Ranking Histogram It tf.idf Frequency >21 Ranking of Target Slides The histogram illustrates that many selected appearances are listed earlier by our approach and about a half of them are treated as the top ranking March 9, 2004 Haruo Yokota (GSIC, Titech) 24

25 Experimental Results Calculating Precisions Precision of the proposed method is 59.4% while tf.idf is 32.2% for the same condition The results demonstrate that proposed impression indicator is effective to search for a presentation scene in presentation databases March 9, 2004 Haruo Yokota (GSIC, Titech) 25

26 UPRISE & KS Presentation slides and recorded video streams are stored in the KnowledgeStore Utilize several functionalities of KS Content retrieval of slides and videos Metadata and full text search for slides Dedicated Indexes corresponding to the impression indicators Single sign-on function March 9, 2004 Haruo Yokota (GSIC, Titech) 26

27 Dataflow Between UPRISE & KS Presentation Slides (ppt) Digital Video Conversion Into pdf Extract Structure Info. Synchronize Create Metadata & Index Conversion Into avi Web-Service APIs Documents Metadata Index Video Stream Web-Service APIs Search & User Interface KnowledgeStore March 9, 2004 Haruo Yokota (GSIC, Titech) 27

28 Synchronization To synchronize the presentation slides and the video We have developed a system by using character recognition techniques for the video stream It enable past presentations to be retrieved It also utilizes information of a laser pointer As a collaborative work with Fujitsu Labs. March 9, 2004 Haruo Yokota (GSIC, Titech) 28

29 Search Interface of UPRISE When keywords are specified, UPRISE searches the table of metadata for tuples matching the given keywords using the index for the table UPRISE calculates the impression indicators with the given keywords Web-based interface showing thumbnails of the slides is developed The size of each thumbnail is varied by the impression indicator. When a thumbnail is clicked, the video is started by the portion showing the slide of the thumbnail. March 9, 2004 Haruo Yokota (GSIC, Titech) 29

30 Snapshot of Searching a Slide Input Keyword Click Synchronizing Display of the Video & Slides Each line indicates part of a sequence of presented slides The size of each thumbnail is varied by the impression indicator March 9, 2004 Haruo Yokota (GSIC, Titech) 30

31 Other External Systems & KS Asunaro (An e-learning system to study Japanese) KS manages the multi-lingual manuscripts and databases for language translation The related materials, such as video stream for foreign language study, are also stored in the KS PRESRI (A citation index) KS stores the research papers and providing search functions for them The PRESRI can also use RDB in KS to store the citation information Research Mining (A research macro-flows discoverer) It can share the research papers and citation information for the PRESRI stored in the KS March 9, 2004 Haruo Yokota (GSIC, Titech) 31

32 Hardware Configuration (1/3) Use a Fiber Channel (FC) switch to configure a storage area network (SAN) 2Gbps 16 ports FC switch To connect a number of servers with FC-RAID having the storage virtualization mechanism to manage storage space by sharing a pooled logical storage volumes Total capacity is 9 TB The configuration easily enable to scale up storage capacity processing performance by changing the number of disks and servers. March 9, 2004 Haruo Yokota (GSIC, Titech) 32

33 Hardware Configuration (2/3) Assign services to a number of servers: video stream servers web servers relational database, XML management servers single sign-on servers contents creation servers to enhance the freedom in the extension of servers It allows adjusting the processing performance for service by service. March 9, 2004 Haruo Yokota (GSIC, Titech) 33

34 Hardware Configuration (3/3) For preserving the reliability of the system Additional ATA RAIDs for backup Nowadays, cheap RAIDs tend to be used as backup devices instead of magnetic-tape drives from cost-performance point of view Three 3TB RAIDs (Totally 9TB) Connected to the SAN Automatic backup from primary RAID to backup RAID without using LAN (LAN free backup) Uninterruptible power supplies (UPSs) March 9, 2004 Haruo Yokota (GSIC, Titech) 34

35 Hardware Configuration Overview The Internet client SSO SSO Server LAN (Gbit Ether Switch) Video Stream Server Web Server RDB / XML Server Contents Creation RAIDs 9TB Video/ Sound Contents SAN (2Gbps 16port FC Switch) Documents Contents Metadata Index Backup RAIDs 9 TB Scanner Camera etc. March 9, 2004 Haruo Yokota (GSIC, Titech) 35

36 Specifications of Servers (1/2) Video Stream Server UltraSparcIIIi 1.062GHz x 4 8GB Memory and 36GB x 4 HDD Solaris 8 and Helix Universal Server Web Server UlltraSparcIIIi 1.062GHz x 4 8GB Memory and 36GB x 4 HDD Solaris 8 and Sun ONE Application Server7 RDB / XML Server Pentium Xeon 3.06GHz x 2 4GB Memory and 18.6 GB HDD Redhat Enterprise Linux Advanced Sever 3 Oracle 9i and Tamnio XML DB March 9, 2004 Haruo Yokota (GSIC, Titech) 36

37 Specifications of Servers (2/2) Single Sign-On Server for Video Stream Access Pentium Xeon 3.06GHz x 2 1GB Memory and 18.6 GB HDD Redhat Linux 9 Single Sign-On Server for Web Access Pentium Xeon 3.06GHz x 2 2GB Memory and 36.4 GB HDD Redhat Linux 9 Contents Creation Server Pentium Xeon 3.06GHz x 2 2GB Memory and 18.6 GB HDD Windows XP Professional March 9, 2004 Haruo Yokota (GSIC, Titech) 37

38 Very Hot News The hardware is being set up TODAY! March 9, 2004 Haruo Yokota (GSIC, Titech) 38

39 Switches and Servers March 9, 2004 Haruo Yokota (GSIC, Titech) 39

40 Concluding Remarks (1/2) We proposed a combination of an information storage system and external systems by web-service APIs to the Titech COE LKR project. The information storage system named KnowledgeStore provides common functions for handling the variety of data formats The external systems execute special applications based on the knowledge resources such as presentation retrieval, e- learning, and research macro-flows discovery March 9, 2004 Haruo Yokota (GSIC, Titech) 40

41 Concluding Remarks (2/2) The configuration realize the flexibility and extensibility required for managing the large-scale knowledge resources. Currently Implementing the KnowledgeStore and external systems Considering the enhancement of functions, such as managing versions. March 9, 2004 Haruo Yokota (GSIC, Titech) 41

42 Thanks for your attention March 9, 2004 Haruo Yokota (GSIC, Titech) 42