Project Report: Intelligent Semantic Oriented Agent Based Search (I-SOAS)

Total Page:16

File Type:pdf, Size:1020Kb

Project Report: Intelligent Semantic Oriented Agent Based Search (I-SOAS) Project Report: Intelligent Semantic Oriented Agent based Search (I-SOAS) Author: Zeeshan AHMED 1 PeerJ PrePrints | https://dx.doi.org/10.7287/peerj.preprints.1518v1 | CC-BY 4.0 Open Access | rec: 19 Nov 2015, publ: 19 Nov 2015 Contact Information: Author: Zeeshan Ahmed Phone: 0043 158801 30726 Cell: 0043 699 81302854 Office Address: Getreidemarkt 9/307 1060 Vienna Austria E-Mail: [email protected] University advisor: Univ.-Prof. Dr.-Ing. Detlef Gerhard Phone: 0043 158801 30722 Email: [email protected] Mechanical Engineering Informatics and Phone: +43 158801 30721 Virtual Product Development Division (MIVP) Fax: + 43 158801 3098 Vienna University of Technology Internet: mivp.tuwien.ac.at Getreidemarkt 9/307 1060 Wien Austria 2 PeerJ PrePrints | https://dx.doi.org/10.7287/peerj.preprints.1518v1 | CC-BY 4.0 Open Access | rec: 19 Nov 2015, publ: 19 Nov 2015 ABSTRACT Product Data Management (PDM) produced desktop and web based systems to maintain the organizational technical and managerial data to increase the quality of products by improving the processes of development, business process flows, change management, product structure management, project tracking and resource planning. Though PDM is heavily benefiting industry but PDM community is facing some serious unresolved issues in PDM System development. i.e., unfriendly graphical user interfaces and unintelligent search. PDM Systems offer different many services and functionalities at a time but the graphical user interfaces of most of the PDM Systems are not designed in a way that a user (especially a new user) can easily learn and use them. Moreover, PDM Systems contain and manage heavy amount of data but the search mechanism of most of the PDM System is not intelligent which can process user’s structured or unstructured natural language based queries to extract desired information. Targeting above discussed two serious PDM based issues a thorough research is conducted in fields of Product Data Management (PDM), Human Machine Interfaces (HMI) and Semantic Web (SW). Concerning PDM, conducted research discusses PDM desktop and web based systems, PDM system development guidelines and some existing PDM Systems. Concerning HMI, conducted research provide information about HMI Designing including Ideologies, Principles, Patterns, Design Guidelines, Basic Design Goals, Problems and Rich Internet Applications (RIA) for Web based HMI Development. Concerning SW, conducted research provides information about Web based information modeling and processing, Ontologies and semantic oriented information modeling based approaches. Using conducted research based information and keeping some existing solutions toward targeted PDM community’s issues in mind a semantic oriented, information processing and intelligent graphical user interface based solution is proposed. i.e., Intelligent Semantic Oriented Agent based Search (I-SOAS). Describing the proposition in detail the main concept, implementation designs and developed prototype of I-SOAS is discussed in this dissertation. Keywords: Agents, Product Data Management, Human Machine Interface, Information Modeling, Search, Semantic web, Web 3 PeerJ PrePrints | https://dx.doi.org/10.7287/peerj.preprints.1518v1 | CC-BY 4.0 Open Access | rec: 19 Nov 2015, publ: 19 Nov 2015 TABLE OF CONTENTS Contents 1 Introduction ....................................................................................................... 10 1.1 Preface .......................................................................................................................................... 10 1.2 Goals of Research ........................................................................................................................ 10 1.3 Scope of research ......................................................................................................................... 11 1.4 Structure of Research ................................................................................................................... 12 1.5 Structure of Dissertation .............................................................................................................. 14 2 Product Data Management (PDM) ................................................................... 15 2.1 Introduction to PDM .................................................................................................................... 15 2.2 PDM Systems .............................................................................................................................. 16 2.3 Challenges to PDM ...................................................................................................................... 16 2.3.1 Static and Unfriendly Graphical User Interface ....................................................................... 16 2.3.2 Static and Unintelligent Search ................................................................................................ 16 2.4 Related Work ............................................................................................................................... 17 2.4.1 K2 Mobility SVT: VIF [81] ..................................................................................................... 17 2.4.2 VIVACE: EU [82] .................................................................................................................... 19 2.4.3 Promise PLM: EU [84] ............................................................................................................. 19 2.4.4 Component-based Product Data Management system [63] ..................................................... 20 2.4.5 Web-based product data management (WPDM) [64] ............................................................. 21 3 Designing Human Machine Interface .............................................................. 23 3.1 Human Machine Interface (HMI) ................................................................................................ 23 3.2 HMI Ideologies ............................................................................................................................ 23 3.3 HMI Design Principles ................................................................................................................ 24 3.4 HMI Design Patterns ................................................................................................................... 25 3.5 HMI Design Goals and Guidelines ............................................................................................. 25 3.6 RIA for Web based HMI Development ...................................................................................... 26 3.7 HMI: Related Work ..................................................................................................................... 28 3.7.1 Windchill [85] ........................................................................................................................... 28 3.7.2 CIM Database [86] ................................................................................................................... 29 4 Web based Information Processing .................................................................. 31 4.1 Web .............................................................................................................................................. 31 4.2 Web to Semantic Web ................................................................................................................. 31 4.3 Current Challenges of Semantic Web ......................................................................................... 32 4.4 Goals of Semantic Web ............................................................................................................... 32 4.5 Semantic Oriented Approaches ................................................................................................... 33 4.5.1 Ontology ................................................................................................................................... 33 4.5.2 Language Technology .............................................................................................................. 36 4.5.3 Semantic desktop: Personal Information Model (PIM) [22] ................................................... 38 4.5.4 Reisewissen [11] ....................................................................................................................... 39 4.5.5 Test Application [26] ................................................................................................................ 39 4.5.6 Meta Data Search Layer [27] ................................................................................................... 40 4 PeerJ PrePrints | https://dx.doi.org/10.7287/peerj.preprints.1518v1 | CC-BY 4.0 Open Access | rec: 19 Nov 2015, publ: 19 Nov 2015 4.5.7 Cultural Heritage and the Semantic Web [38] ......................................................................... 41 4.5.8 Semantic Security Web Services (SSWS) [30] ........................................................................ 41 4.5.9 Partial Distance Map (PDM) [62] ............................................................................................ 41 5 I-SOAS Approach ............................................................................................. 43 5.1 Intelligent User Interface ............................................................................................................. 44
Recommended publications
  • LNCS 3532, Pp
    Activity Based Metadata for Semantic Desktop Search Paul Alexandru Chirita, Rita Gavriloaie, Stefania Ghita, Wolfgang Nejdl, and Raluca Paiu L3S Research Center / University of Hanover, Deutscher Pavillon, Expo Plaza 1, 30539 Hanover, Germany {chirita, gavriloaie, ghita, nejdl, paiu}@l3s.de Abstract. With increasing storage capacities on current PCs, searching the World Wide Web has ironically become more efficient than searching one’s own per- sonal computer. The recently introduced desktop search engines are a first step towards coping with this problem, but not yet a satisfying solution. The reason for that is that desktop search is actually quite different from its web counter- part. Documents on the desktop are not linked to each other in a way compara- ble to the web, which means that result ranking is poor or even inexistent, be- cause algorithms like PageRank cannot be used for desktop search. On the other hand, desktop search could potentially profit from a lot of implicit and explicit semantic information available in emails, folder hierarchies, browser cache con- texts and others. This paper investigates how to extract and store these activity based context information explicitly as RDF metadata and how to use them, as well as additional background information and ontologies, to enhance desktop search. 1 Introduction The capacity of our hard-disk drives has increased tremendously over the past decade, and so has the number of files we usually store on our computer. It is no wonder that sometimes we cannot find a document any more, even when we know we saved it somewhere. Ironically, in quite a few of these cases nowadays, the document we are looking for can be found faster on the World Wide Web than on our personal com- puter.
    [Show full text]
  • Master Thesis Innovation Dynamics in Open Source Software
    Master thesis Innovation dynamics in open source software Author: Name: Remco Bloemen Student number: 0109150 Email: [email protected] Telephone: +316 11 88 66 71 Supervisors and advisors: Name: prof. dr. Stefan Kuhlmann Email: [email protected] Telephone: +31 53 489 3353 Office: Ravelijn RA 4410 (STEPS) Name: dr. Chintan Amrit Email: [email protected] Telephone: +31 53 489 4064 Office: Ravelijn RA 3410 (IEBIS) Name: dr. Gonzalo Ord´o~nez{Matamoros Email: [email protected] Telephone: +31 53 489 3348 Office: Ravelijn RA 4333 (STEPS) 1 Abstract Open source software development is a major driver of software innovation, yet it has thus far received little attention from innovation research. One of the reasons is that conventional methods such as survey based studies or patent co-citation analysis do not work in the open source communities. In this thesis it will be shown that open source development is very accessible to study, due to its open nature, but it requires special tools. In particular, this thesis introduces the method of dependency graph analysis to study open source software devel- opment on the grandest scale. A proof of concept application of this method is done and has delivered many significant and interesting results. Contents 1 Open source software 6 1.1 The open source licenses . 8 1.2 Commercial involvement in open source . 9 1.3 Opens source development . 10 1.4 The intellectual property debates . 12 1.4.1 The software patent debate . 13 1.4.2 The open source blind spot . 15 1.5 Litterature search on network analysis in software development .
    [Show full text]
  • Instructions for the Preparation of a Camera-Ready Paper in MS Word
    Review Semantic web; towards Ontology based Web Application Editor(s): Name Surname, University, Country Solicited review(s): Name Surname, University, Country Open review(s): Name Surname, University, Country Zeeshan Ahmed*, Saman Majeed Department of Bioinformatics, Biocenter, University of Wuerzburg, Am Hubland 97074, Wuerzburg Germany Abstract. In this review we address the importance of field i.e. Semantic Web; a mechanism of presenting information over the web in a format so that human being as well as machines can understand the semantic of context. Describing the techno- logical contributions of Semantic Web in detail, we present its main innovation i.e. Ontology, and development supporting technologies i.e. XML (eXtensible Mark-up Language), RDF (Resource Description Framework) and OWL (Web Ontology Language), offering different ways of more explicitly structuring and richly annotating Web pages. Furthermore, in this review paper, we discuss how ontology is contributing to semantic web development with the presentation of some Semantic Web application and conclude with some existing limitations need to be overcome. Keywords: Web, Ontology, Semantic Web 1. Introduction easy to go for scattered extensive information by looking into bookmarked web pages but quite diffi- Targeting the challenge of implementing a web cult to extract a piece of needed information. Al- based system capable of performing semantic based though some search engines and screen scrapers are search to extract desired information from attached invented, search
    [Show full text]
  • Cognitive Aspects of Semantic Desktop to Support
    COGNITIVE ASPECTS OF SEMANTIC DESKTOP TO SUPPORT PERSONAL INFORMATION MANAGEMENT by Danish Nadeem A thesis submitted to the Institute of Cognitive Science in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE Thesis Advisors Prof.Dr. Kai-Christoph Hamborg Dipl.Inf. Leo Sauermann University of Osnabrueck March 2007 Copyright c 2007 Danish Nadeem All Rights Reserved DECLARATION I declare that the Master Thesis entitled: Cognitive Aspects of Semantic Desk- top to Support Personal Information Management is my own original work, and hereby certify that unless stated, all work contained within this thesis is my own independent research and has not been submitted for the award of any other degree at any institution, except where due acknowledgment is made in the text. ERKLAERUNG Mit der Abgabe die Diplomarbeit mit dem Thema: Cognitive Aspects of Se- mantic Desktop to Support Personal Information Management, versichere ich, dass ich selbststndig verfasst und keine anderen als die angegebenen Quellen und Hilfsmittel benutzt habe. Die Stellen, die anderen Werken dem Wort- laut oder dem Sinn nach entnommen wurden, habe ich durch die Angabe der Quelle, auch der benutzten Sekundrliteratur, als Entlehnung kenntlich gemacht. Date Danish Nadeem UNIVERSITY OF OSNABRUECK As the main supervisor of the candidate's graduate committee, at the Uni- versity of Osnabrueck, I have read the dissertation of Danish Nadeem in its final form and have found that (1) its format, citations, and bibliographical style are consistent and acceptable and fulfill university and department style requirements; (2) its illustrative materials including figures and tables are in place; and (3) the final manuscript is satisfactory to the graduate committee and is ready for submission to the university record.
    [Show full text]
  • Personal Knowledge Models with Semantic Technologies
    Max Völkel Personal Knowledge Models with Semantic Technologies Personal Knowledge Models with Semantic Technologies Max Völkel 2 Bibliografische Information Detaillierte bibliografische Daten sind im Internet über http://pkm. xam.de abrufbar. Covergestaltung: Stefanie Miller Herstellung und Verlag: Books on Demand GmbH, Norderstedt c 2010 Max Völkel, Ritterstr. 6, 76133 Karlsruhe This work is licensed under the Creative Commons Attribution- ShareAlike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/3.0/ or send a letter to Creative Commons, 171 Second Street, Suite 300, San Fran- cisco, California, 94105, USA. Zur Erlangung des akademischen Grades eines Doktors der Wirtschaftswis- senschaften (Dr. rer. pol.) von der Fakultät für Wirtschaftswissenschaften des Karlsruher Instituts für Technologie (KIT) genehmigte Dissertation von Dipl.-Inform. Max Völkel. Tag der mündlichen Prüfung: 14. Juli 2010 Referent: Prof. Dr. Rudi Studer Koreferent: Prof. Dr. Klaus Tochtermann Prüfer: Prof. Dr. Gerhard Satzger Vorsitzende der Prüfungskommission: Prof. Dr. Christine Harbring Abstract Following the ideas of Vannevar Bush (1945) and Douglas Engelbart (1963), this thesis explores how computers can help humans to be more intelligent. More precisely, the idea is to reduce limitations of cognitive processes with the help of knowledge cues, which are external reminders about previously experienced internal knowledge. A knowledge cue is any kind of symbol, pattern or artefact, created with the intent to be used by its creator, to re- evoke a previously experienced mental state, when used. The main processes in creating, managing and using knowledge cues are analysed. Based on the resulting knowledge cue life-cycle, an economic analysis of costs and benefits in Personal Knowledge Management (PKM) processes is performed.
    [Show full text]
  • Access Control for Sharing Semantic Data Across Desktops
    Access Control for Sharing Semantic Data across Desktops ? Juri L. De Coi, Ekaterini Ioannou, Arne Koesling, Wolfgang Nejdl, Daniel Olmedilla L3S Research Center/Leibniz Universit¨atHannover Appelstr. 9a, 30167 Hanover, Germany {lastname}@L3S.de Abstract. Personal Information Management (PIM) systems aim to pro- vide convenient access to all data and metadata on a desktop to the user itself as well as the co-workers. Obviously, sharing desktop data with co-workers raises privacy and access control issues which have to be ad- dressed. In this paper we discuss these issues, and present appropriate solutions. In line with the architecture of current PIM systems [8, 2, 11, 15], our solutions cover all semantic data shared in such a context, i.e. all desktop resources as well as other data structures created by the system, such as metadata in an RDF store and inverted index entries created for efficient textual search. We discuss different kinds of policies to specify protection for desktop data and metadata, and describe our access con- trol system to express and execute these policies efficiently. Additionally, we describe the extension of an existing PIM system, Beagle++, with our approach, as well as our experiments, with convincing results on perfor- mance and scalability. 1 Introduction In recent years, the amount of available digital information has increased con- siderably not only on the Web but also on personal computers. New innovative Personal Information Management (PIM) systems support users in organizing and managing their calendars, e-mails, address books, and other information on their desktop. PIM systems like Google Desktop [8], Beagle [2], Haystack [11], and Gnowsis [15], define semantic data as all content of the personal information space.
    [Show full text]
  • Augmenting Autobiographical Memory: an Approach Based on Cognitive Psychology
    http://researchcommons.waikato.ac.nz/ Research Commons at the University of Waikato Copyright Statement: The digital copy of this thesis is protected by the Copyright Act 1994 (New Zealand). The thesis may be consulted by you, provided you comply with the provisions of the Act and the following conditions of use: Any use you make of these documents or images must be for research or private study purposes only, and you may not make them available to any other person. Authors control the copyright of their thesis. You will recognise the author’s right to be identified as the author of the thesis, and due acknowledgement will be made to the author where appropriate. You will obtain the author’s permission before publishing any material from the thesis. Augmenting Autobiographical Memory: An Approach Based on Cognitive Psychology A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy in Computer Science at The University of Waikato by Andrea Schweer Department of Computer Science Hamilton, New Zealand 2011 © 2011 Andrea Schweer Dedicated to the memory of Liesel Schweer née Maas Abstract This thesis investigates how an interactive software system can support a person in remembering their past experiences and information related to these experiences. It proposes design recommendations for augmented autobiographical memory systems derived from Cognitive Psychology re- search into human memory – a perspective missing from prior work. Based on these recommendations, a conceptual design of an augmented autobiographical memory system is developed that aims to support users in retrieving cues and factual information related to experiences as well as in reconstructing those experiences.
    [Show full text]
  • Semantic Clipboard - Semantically Enriched Data Exchange Between Desktop Applications
    Semantic Clipboard - Semantically Enriched Data Exchange Between Desktop Applications Gerald Reif, Martin Morger, and Harald Gall University of Zurich, Department of Informatics, 8050 Zurich, Switzerland {reif,gall}@ifi.unizh.ch [email protected], WWW home page: http://seal.ifi.unizh.ch/ Abstract. The operating system clipboard is used to copy and paste data between applications even if the applications are from different ven- dors. Current clipboards only support the transfer of data or formatted data between applications. The semantics of the data, however, is lost in the transfer. The Semantic Web, on the other hand, provides a common framework that allows data to be shared across application boundaries while preserving the semantics of the data. In this paper we introduce the concept of a Semantic Clipboard and present a prototype implementation that can be used to copy and paste RDF meta-data between desktop applications. The Semantic Clipboard is based on a flexible plugin architecture that enables the easy extension of the clipboard to new ontology vocabularies and target applications. Furthermore, we show how the Semantic Clipboard is used to copy and paste the meta-data from semantically annotated Web pages to a user’s desktop application. 1 Introduction Users frequently use the clipboard of the operating system to exchange data between desktop applications. They select the data they want to copy in the source application, the data is then temporarily stored by the clipboard, and inserted into the target application selected by the user. With current clipboard applications the data is transferred as text or binary data. The semantics of the data, however, is lost.
    [Show full text]
  • Improving Personal Information Management by Integrating Activities in the Physical World with the Semantic Desktop
    Improving Personal Information Management by Integrating Activities in the Physical World with the Semantic Desktop Yingjie Hu Krzysztof Janowicz Department of Geography Department of Geography University of California Santa Barbara University of California Santa Barbara [email protected] [email protected] ABSTRACT 1. INTRODUCTION AND MOTIVATION Semantic desktops are a novel approach to improve user in- Each of us is creating and maintaining an increasing terfaces by recording, semantically annotating, and learning amount of personal information, such as emails, ToDo lists, from the user's activities to create a personalized user ex- pictures, bookmarks, or notes. The volume and variety of perience and improve search. Such activities, however, are information created by consumer electronics, reveal the lim- restricted to the information universe, i.e., they only cover itation of traditional information organization mechanisms events on the local desktop. A next step towards smart such as those based on hierarchical directories. Users have to mobile devices is the integration of those desktop events pre-define and constantly maintain a folder structure as well with the user's activities in the physical world. Establishing as decide on how to file a particular information object. A such mappings enables the device to draw conclusions from recent study analyzing email organization shows that even the recorded desktop events to those that the user is likely well structured folders do not provide better performance performing in the physical world. A Personal Information than using the search-file function[12]. One reason for this is Management (PIM) system can then better assist the user that the same information item can be categorized according in task planning and routing.
    [Show full text]
  • Poster Template
    Improving Personal Information Management by Using Activities in the Physical World to Bridge the Semantic Web and the Semantic Desktop Yingjie Hu and Krzysztof Janowicz Department of Geography, University of California Santa Barbara Abstract 2. Activities in the Physical World and Their Digital Footprints Personal information refers to the information used by individuals to Information from both the Semantic Web and the Semantic Desktop are employed by complete their daily tasks and is not intended to share with the public. Such individuals to complete their activities in the physical world. Meanwhile, people’s activities information can come from two major sources: the Web and personal devices in the physical world often have their corresponding digital footprints in the two information such as laptops. The Semantic Web is a technology stack which provides universes. For example, when preparing a paper for a conference, people may create and edit capabilities to organize the information on the web, while the Semantic a document on their laptops, and may also open several related papers at the same time. Desktop can associate the related data and files on people’s personal devices. Similarly, the conference, which contains a series of human activities, also has its In order to complete everyday tasks, people often need to combine the corresponding footprints, such as an official page, a record in Freebase or in WikiCFP, on information from both of the two sources. However, the two information the web. Figure 2 shows the relations among activities in the physical world and their universes are not directly connected. In this work, we propose to use activities corresponding digital footprints on the Semantic Web and the Semantic Desktop.
    [Show full text]
  • Linking Semantic Personal Notes*
    Linking Semantic Personal Notes? Laura Dr˘agan,Alexandre Passant, Tudor Groza, and Siegfried Handschuh DERI, National University of Ireland, Galway, IDA Business Park, Lower Dangan, Galway, Ireland [email protected] http://www.deri.ie/ Abstract. Semantic Web technologies are available and gain popularity both on the Web and on the desktop. However, in spite of common rep- resentation formats, personal and online data is still difficult to interlink, notably because of the different vocabularies used to describe it, as well as the lack of common identifiers between desktop and Web-based ap- plications. In this paper, we describe a process for easily publishing and sharing of personal notes as Linked Data. Our approach can be used to publish any kind of information from the desktop to the Web, enabling integration of small chunks of personal knowledge into the Web of Data and focusing on a user-driven approach of knowledge management. 1 Introduction Semantic Web technologies are now deployed in various domains and applica- tions. Among the different sub-domains of the broader Semantic Web vision, two relevant fields are the Linked Data initiative, focusing on global interlink- ing on the Web, and the Semantic Desktop, focusing on personal information integration. While these two domains share compatible representation models (RDF(S)/OWL), there is still a gap between data from the Web and the desk- top. Among others, vocabularies that they use are generally not well integrated and identifiers (URIs) are generally distinct. Such gap can be explained as the Semantic Desktop focused on using local identifiers and desktop-related ontolo- gies, while the Linking Open Data (LOD) initiative focused on the global reuse of identifiers and ontologies.
    [Show full text]
  • Application Design and Interoperability for Managing Personal Information in the Semantic Desktop?
    Application Design and Interoperability for Managing Personal Information in the Semantic Desktop? Huiyong Xiao Isabel F. Cruz Department of Computer Science University of Illinois at Chicago fhxiao j [email protected] Abstract. A number of semantic desktop frameworks have been proposed that address different issues in personal information management, including the or- ganization, manipulation, and visualization of personal data. Our approach com- prises a layered multi-ontology based framework, MOSE. In this paper, we de- scribe how the architecture of MOSE supports an application centered seman- tic approach to personal information management. In particular, we introduce a method based on the Model-View-Controller paradigm for personal information application (PIA) development, as enabled by the underlying semantic data or- ganization and specified by the PIA designer. We also introduce the notion of parameterized channel and describe how it supports the interaction among mul- tiple visualizations in a PIA. We give a definition of desktop service based on the concept of parameterized channel and the benefits provided by the separation of PIA definition and implementation. Finally, we discuss two cases of the execution of desktop services in MOSE that highlight application interoperability. 1 Introduction With the development of computer device manufacturing, storage is no longer a bottle- neck for computer users. As users will not have to remove outdated data from storage, the increasingly large amount of data poses a critical problem: the organization of the personal information space so as to enable efficient and effective data management. Typically, personal information in a desktop is characterized by: (1) Disparate mod- els: the personal data tend to be of different formats and use different models for data storage and presentation.
    [Show full text]