Business Information Systems (eBook)

0047 2
Preface 5
Organization 6
Table of Contents 8
Session 1. Search and Knowledge Sharing 8
Faceted Wikipedia Search 11
Introduction 11
UserInterface 12
DBpedia 14
The DBpedia Extraction Framework 14
The DBpedia Knowledge Base 15
Faceted Search Implementation 15
Requirements 15
Actual Implementation 17
Related Work 19
Conclusion 20
References 20
A Model of Cross-Functional Coopetition in Software Development Project Teams 22
Introduction 22
Literature Review 23
Theoretical Modeling 25
Hypothesises 25
Development of the Preliminary Model of Constructs Measurers 27
Research Methodology 28
Multiple Case-Studies 28
Survey Study 30
Research Limitations and Conclusion 30
References 31
Using Probabilistic Topic Models in Enterprise Social Software 33
Introduction 33
Probabilistic Topic Models 34
Basic Assumptions 34
Latent Dirichlet Allocation 35
Training and Using LDA 35
Applying Topic Analysis in Recommender Systems and Search 36
Recommender Systems 36
Using LDA in Search 38
Topic Analysis in Enterprise Social Software 39
Knowledge Structures and Latent Topics 39
Implementation 40
Walkthrough of the System 41
Related Work 42
Conclusions and Further Work 42
References 43
Session 2. Data and Information Security 8
Using SPARQL and SPIN for Data Quality Management on the Semantic Web 45
Introduction 45
Overview of Data Quality Problems 46
Representational Inconsistency 47
Comprehensibility 48
Heterogeneity 48
Redundancy 48
Identifying Data Quality Problems with SPARQL and SPIN 49
Architecture for Ontology-Based Data Quality Management (OBDQM) 49
Identification of Data Quality Problems with SPIN 50
Related Work 53
Evaluation 54
Conclusion and Outlook on Future Work 55
References 55
Quality in Blogs: How to Find the Best User Generated Content 57
Introduction 57
Related Work 58
Link Analysis 59
Page Content and Design 59
Machine Learning Approaches 59
Automatic Assessment of User Generated Content 60
Blog Analysis 61
Quality Model Development 63
Performance of the Trained Quality Models 64
Conclusion and Future Work 67
References 67
Avoiding Inconsistency in User Preferences for Data Quality Aware Queries 69
Introduction 69
Related Works 71
Quality-Aware Queries 73
Quality-Aware Metadata 73
Quality-Aware SQL 73
Modelling User Preferences 74
Inconsistent Partial Order Graphs 75
Inconsistency Detection 77
Evaluation and Conclusion 78
References 80
Session 3. Web Experience Modelling 8
Textractor: A Framework for Extracting Relevant Domain Concepts from Irregular Corporate Textual Datasets 81
Introduction 81
Related Work 83
Textractor Framework 83
Data Pre-processing 84
Candidate Concept Identification 85
Concept Selection and Extraction 86
Evaluation 87
Language Detector 88
Candidate Concept Identification 88
Concept Selection and Extraction 89
Conclusion and Future Work 90
References 91
Comparing Intended and Real Usage in Web Portal: Temporal Logic and Data Mining 93
Introduction 93
LTL over a Kripke Structure as a Common Formalism 95
Modeling a Web Portal to Verify Intended and Real Usages 96
Web Portal Model 97
Intended Usage 98
Frequent Usage Patterns Discovery through Frequent Sequential Pattern Mining 99
Comparing Real Usage and Intended Usage 101
TheWholeProcess 102
Conclusion 103
References 103
Capturing Eye Tracking Data for Customer Profiling 104
Introduction 104
Problem Context and Statement 105
Instrumentation 107
The Proposed Model 107
Profile Processing Prospects 113
Conclusions 113
References 114
Session 4. Business Processes and Rules 9
Consistency Checking of Compliance Rules 116
Introduction 116
Preliminaries 117
Linear Temporal Logic with Past Operators (PLTL) 117
Compliance Rules for Business ProcessModels 118
LTL Model Checking Based on B¨uchi Automata 119
Checking Consistency for Compliance Rules 120
The Business Context 122
Detecting Compliance Conflicts 123
Related Work 126
Conclusion 126
References 127
From Economic Drivers to B2B Process Models: A Mapping from REA to UMM 129
Introduction 129
Input and Output Models for Our Transformation 130
REA - The Input Model 130
UMM - The Output Model 132
Mapping REA to UMM 133
A Real Life Example from the Print Media Domain 133
Conceptual Mapping 135
Transformation Rules 138
Related Work 139
Conclusion 140
References 140
Using Surveys to Evaluate a Business Rules Based Development Approach 142
Introduction 142
Motivation 143
Business Rules Development Approach 144
K-Site Rules Business Rules Management System 145
K-Site Rules Expert Editor Evaluation 146
Survey Execution Environment 148
Survey Description 148
Time per Task 149
Participants' Characterization 149
K-Site Rules Interaction 151
Conclusions and Future Work 152
References 153
Session 5. Services and Repositories 9
Identification of Services through Functional Decomposition of Business Processes 154
Introduction 154
Related Work 155
Fundamental Concepts 156
Natural Types and Role Types 157
Activities 159
Functional Decomposition 159
Role Ontology 162
Actor (Who) 162
Resource (What) 163
Locator (Where) 163
Goal, Rule (Why) 163
Starter, Finisher (How, When) 163
Research Methodology 163
Conclusion and Future Work 164
References 165
Requirements for a Business Process Model Repository: A Stakeholders’ Perspective 168
Introduction 168
Research Approach 169
Exploratory Study 170
Analysis 170
Propositions 171
Empirical Study 172
Empirical Analysis 173
Requirements of Process Model Repository 177
Conclusion 178
References 179
Supporting Complex Business Information Systems A Case Study Focusing on Incidents, Recovery and Evolution 181
Introduction 181
Related Work 182
Terminology 183
Maintainability 185
Case Study’s Scenario 186
Avoiding Incidents 187
Landscape Recovery 189
Evolution 190
Conclusion 191
References 191
Session 6. Data Mining for Processes 9
On Integrating Data Mining into Business Processes 193
Introduction 193
Business Process Management 194
Business Processes and User Groups 194
Business Process Reengineering and Its Evaluation 195
Data Mining 196
Data Mining Problems, Goals and Methods 196
The Data Mining Process 196
Evaluating Data Mining 197
Integration of BPM and Data Mining 197
An Integrated Role Model 198
Integration of Data Mining Processes into Business Processes 199
Evaluating the Integration 200
Related Work 201
Conclusion 203
References 203
From Process Execution towards a Business Process Intelligence 205
Introduction 205
Process Orientation and Concepts of Process Analyses 206
Business Process Management 207
Current Concepts of Process Analyses 207
Systematization of Business Process Intelligence 209
Research Framework 210
Conclusion 215
References 215
Auditing Workflow Executions against Dataflow Policies 217
Introduction 217
WorkflowsandLogData 218
Policies 219
Syntax 220
Semantics 221
Audit Algorithm 222
Related Work 224
Conclusion and Ongoing Work 225
References 226
Workflow Data Footprints 228
Introduction 228
WFD-Nets for the Modeling of (Business) Workflows 230
Generation of Data Footprints 234
Conclusions 238
References 239
Session 7. Visualisation in BPM 9
On the Cognitive Effectiveness of Routing Symbols in Process Modeling Languages 240
Introduction 240
The Cognitive Side to Process Modeling 241
Evaluating the Cognitive Effectiveness of Modeling Languages 244
Language Differences 245
Basic Elements of Process Modeling Languages 245
Event-Driven Process Chains (EPCs) 246
UML Activity Models 246
Yet Another Workflow Language (YAWL) 247
Business Process Modeling Notation (BPMN) 247
Evaluation and Discussion 248
Conclusion 249
References 250
Visualising Business Capabilities in the Context of Business Analysis 252
Introduction 252
Business Capabilities and Business Analysis 253
Business Capabilities 253
Business Analysis Based on Business Capabilities 254
Visualisation of Business Capabilities 256
Example Visualisation 259
Related Work 261
Conclusion and Future Work 262
References 262
A Model Driven Engineering Approach for Modelling Versions of Business Processes using BPMN 264
Introduction 264
Modelling Versions of BPs: The VBP Meta-model 265
Notion of Version 266
VBP Meta-model 266
Extending BPMN to Model Versions of BPs 268
Core BPMN Concepts 268
BPMN Extensions 270
Mapping VBP onto Extended BPMN 271
Concepts and Pattern Mapping 271
QVT Transformation Rule 272
Implementation 273
Extending the BPMN Modeller Plug-In 273
Illustrative Example 274
Conclusion 275
References 276
Session 8. ERP and SCM 10
Value Propositions in Service Oriented Business Models for ERP: Case Studies 278
Introduction 278
Theoretical Framework 279
Service Orientation 279
Enterprise Resource Planning 279
ERP and Service Orientation 280
Business Model and Value Proposition 280
Case Analysis Approach 281
Content of the Value Propositions Found in the Case Studies 281
Assumed Customer Value 281
Patterns of Business Models 282
Findings 282
Case Overview 282
Content of Value Propositions Found in the Case Studies 284
Assumed Customer Value 285
Patterns of Business Model Components 287
Conclusions and Future Research 287
References 288
Event-Driven Business Intelligence Architecture for Real-Time Process Execution in Supply Chains 290
Introduction 290
Use Case for Supply Chain Logistics 291
Operational Business Intelligence 292
Concept of Operational Business Intelligence for Increasing Supply Chain Performance 293
Operational Business Intelligence Architecture for Supply Chain Management 293
Event-Driven Process Components 295
Appraisal of the Approach 297
Conclusion 299
References 299
Production Inventory and Enterprise System Implementation: An Ex-ante No-Cost Based Evaluation 301
Context and Problem Statement 301
ES Three-Step Ex-ante Evaluation Procedure: Application to aProduction Inventory Context 303
Metrics and Benefits: The Selection and Alignment Process 304
Methodology Selection and Business Modelling 306
Performance Metric Analysis and Evaluation of ES Investment 309
Conclusion 310
References 311
Author Index 314

"Faceted Wikipedia Search (S. 1-2)

1 Introduction

This paper presents Faceted Wikipedia Search, an alternative search interface for the English edition of Wikipedia. Faceted Wikipedia Search allows users to ask complex questions, like “Which rivers ?ow into the Rhine and are longer than 50 kilometers?” or “Which skyscrapers in China have more than 50 ?oors and were constructed before the year 2000?” against Wikipedia knowledge. Such questions cannot be answered using keyword-based search as provided by Google, Yahoo, or Wikipedia’s own search engine.

In order to answers such questions, a search engine must facilitate structured knowledge which needs to be extracted from the underlying articles. On the user interface side, a search engine requires an interaction paradigm that enables inexperienced users to express complex questions against a heterogeneous information space in an exploratory fashion. For formulating queries, Faceted Wikipedia Search relies on the faceted search paradigm. Faceted search enables users to navigate a heterogeneous information space by combining text search with a progressive narrowing of choices along multiple dimensions [6,7,5].

The user subdivides an entity set into multiple subsets. Each subset is de?ned by an additional restriction on a property. These properties are called the facets. For example, facets of an entity “person” could be “nationality” and “year-of-birth”. By selecting multiple facets, the user progressively expresses the di?erent aspects that make up his overall question. Realizing a faceted search interface for Wikipedia poses three challenges:

1. Structured knowledge needs to be extracted from Wikipedia with precision and recall that are high enough to meaningfully answer complex queries.
2. As Wikipedia describes a wide range of di?erent types of entities, a search engine must be able to deal with a large number of di?erent facets. As the number of facets per entity type may also be high, the search engine must apply smart heuristics to display only the facets that are likely to be relevant to the user.
3. Wikipedia describes millions of entities. In order to keep response times low, a search engine must be able to e?ciently deal with large amounts of entity data.

Faceted Wikipedia Search addresses these challenges by relying on two software components: The DBpedia Information Extraction Framework is used to extract structured knowledge from Wikipedia [4]. neofonie search, a commercial search engine, is used as an e?cient faceted search implementation.

This paper is structured as follows: Section 2 describes the Faceted Wikipedia Search user interface and explains how facets are used for navigating and ?ltering Wikipedia knowledge. Section 3 gives an overview of the DBpedia Information Extraction Framework and the resulting DBpedia knowledge base. Section 4 describes how the e?cient handling of facets is realized inside neofonie search. Section 5 compares Faceted Wikipedia Search with related work."