The ability to forecast job advertisement demands is vital to enhance the customer retention rate for recruitment companies. On top of that, it is uneconomical to cold call every individual on a regular basis for companies with a large pool of customers. This paper presents a novel approach in...

The ability to forecast job advertisement demands is vital to enhance the customer retention rate for recruitment companies. On top of that, it is uneconomical to cold call every individual on a regular basis for companies with a large pool of customers. This paper presents a novel approach in...

The increasing awareness of data mining technology, along with the attendant increase in the capturing, warehousing, and utilization of historical data to support evidence-based decision making, is leading many organizations to recognize that the effective use of data is the key element in the...

In this paper, we develop a decision-theoretic frameworkfor evaluating data mining systems, which employ classification methods, in terms of their utility in decision-making. The decision-theoretic model provides an economic perspective on the value of â extracted knowledge,â in terms of its...

Extracting information from text is the task of obtaining structured, machineprocessable facts from information that is mentioned in an unstructured manner.It thus allows systems to automatically aggregate information for further analysis, efficient retrieval, automatic validation, or...

In der vorliegenden Dissertation werden zwei neue Data Mining Verfahren und Metho-den zur Extraktion von qualitätsrelevantem Wissen vorgestellt und mit Anwendungen aus der Automobilbranche evaluiert. Diese neuartigen Verfahren erlauben es, in Abhän-gigkeit der zugrunde liegenden Datentypen,...

Extracting information from text is the task of obtaining structured, machine-processable facts from information that is mentioned in an unstructured manner. It thus allows systems to automatically aggregate information for further analysis, efficient retrieval, automatic validation, or...

This thesis utilizes recommender systems to aid the user in contributing to the Social Semantic Web. In this work, we propose a framework that maps domain properties to recommendation technologies. Next, we develop novel recommendation algorithms for improving personalized tag recommendation and...

This paper proposes the use of an integrated information retrieval framework (IIRF) to facilitate the collection of critical information of a manufacturer’s supply network. It explores the requirements for a sustainable survival of manufacturers by aligning information among the entities...

Oil and gas industries archive volumes of heterogeneous data. These companies, by virtue of their diverse operations, comprise of complicated organizational structure. The nature of organizational set-up with several operational units, often results with communication barriers among operational...