Knowledge Search within a Company-WIKI

The usage of Wikis for the purpose of knowledge management within a business company is only of value if the stored information can be found easily. The fundamental characteristic of a Wiki, its easy and informal usage, results in large amounts of steadily changing, unstructured documents. The widely used full-text search often provides search results of insufficient accuracy. In this paper, we will present an approach likely to improve search quality, through the use of Semantic Web, Text Mining, and Case Based Reasoning (CBR) technologies. Search results are more precise and complete because, in contrast to full-text search, the proposed knowledge-based search operates on the semantic layer

Semantic Jira - Semantic Expert Finder in the Bug Tracking Tool Jira

The semantic expert recommender extension for the Jira bug tracking system semantically searches for similar tickets in Jira and recommends experts and links to existing organizational (Wiki) knowledge for each ticket. This helps to avoid redundant work and supports the search and collaboration with experts in the project management and maintenance phase based on semantically enriched tickets in Jira.Comment: published in proceedings of the 9th International Workshop on Semantic Web Enabled Software Engineering (SWESE2013), Berlin, Germany, December 2-5, 201

When will we learn: key factors and potential barriers

The overall aim of this research was to improve the dissemination of Lessons Learned in construction projects so that contractors’ project teams have access to the most relevant lessons at the most appropriate time, in the most appropriate format. The outcome of the research aimed to provide (1) an understanding of the different systems and tools used for recording Lessons Learned amongst major construction contractors; (2) an understanding of the needs in terms of what sort of lessons are required, the level of detail required and how best these should be made available; and (3) an approach on how best to disseminate Lessons Learned. The key objectives of the research were to: 1. Investigate current practice for recording and disseminating Lessons Learned; 2. Identify potential barriers for successfully disseminating Lessons Learned; and 3. Identify key factors affecting company processes to encourage a more systematic dissemination of Lessons Learned. The study was conducted in three phases. The first investigated contractors’ current practices for recording and disseminating Lessons Learned through a questionnaire survey. The second phase identified key factors that would encourage the institutionalisation of Lessons Learned and also the factors that inhibit their use. The third phase examined how current processes could be adapted to develop a process that would embed the systematic dissemination of Lessons Learned within an organisation’s existing practices. This report focuses on the second stage of the project that identified from the end users those factors that would encourage the institutionalisation of Lessons Learned and also the factors that inhibit their use of Lessons Learned

Finding Patterns in a Knowledge Base using Keywords to Compose Table Answers

We aim to provide table answers to keyword queries against knowledge bases. For queries referring to multiple entities, like "Washington cities population" and "Mel Gibson movies", it is better to represent each relevant answer as a table which aggregates a set of entities or entity-joins within the same table scheme or pattern. In this paper, we study how to find highly relevant patterns in a knowledge base for user-given keyword queries to compose table answers. A knowledge base can be modeled as a directed graph called knowledge graph, where nodes represent entities in the knowledge base and edges represent the relationships among them. Each node/edge is labeled with type and text. A pattern is an aggregation of subtrees which contain all keywords in the texts and have the same structure and types on node/edges. We propose efficient algorithms to find patterns that are relevant to the query for a class of scoring functions. We show the hardness of the problem in theory, and propose path-based indexes that are affordable in memory. Two query-processing algorithms are proposed: one is fast in practice for small queries (with small patterns as answers) by utilizing the indexes; and the other one is better in theory, with running time linear in the sizes of indexes and answers, which can handle large queries better. We also conduct extensive experimental study to compare our approaches with a naive adaption of known techniques.Comment: VLDB 201

BlogForever D2.6: Data Extraction Methodology

This report outlines an inquiry into the area of web data extraction, conducted within the context of blog preservation. The report reviews theoretical advances and practical developments for implementing data extraction. The inquiry is extended through an experiment that demonstrates the effectiveness and feasibility of implementing some of the suggested approaches. More specifically, the report discusses an approach based on unsupervised machine learning that employs the RSS feeds and HTML representations of blogs. It outlines the possibilities of extracting semantics available in blogs and demonstrates the benefits of exploiting available standards such as microformats and microdata. The report proceeds to propose a methodology for extracting and processing blog data to further inform the design and development of the BlogForever platform

Introducing "2.0" functionalities in an ERP

Companies and ERP editors show an increasing interest for the Web 2.0 technologies, aiming at involving the user of a web site in the creation of content. We summarize in this communication what these tools are and give an overview of recent examples of their use in companies. We show on the example of the most recent ERP of SAP, Business By Design, that if "2.0 tools" are now available in some ERPs, their integration in the business processes is not yet fully done. We suggest in that purpose the first draft of a methodology aiming at developing "2.0 business processes" using an ERP 2.0

Collaborative knowledge management - A construction case study

Due to the new threats and challenges faced by the construction industry today, construction companies must seek new solutions in order to remain ahead of the competition. Knowledge has been identified to be a significant organisational resource, which if used effectively can provide competitive advantage. A lot of emphasis is being put on how to identify, capture and share knowledge in today's organisations. It has been argued over the years that due to the fragmented nature of the construction industry and ad-hoc nature of the construction projects, capture and reuse of valuable knowledge gathered during a construction project pose a challenge. As a result critical mistakes are repeated on projects and construction professionals have to kee