Text mining is an exciting application ?eld and an area of scienti?c - search that is currently under rapid development. It uses techniques from well-established scienti?c ?elds (e. g. data mining, machine learning, infor- tion retrieval, natural language processing, case-based reasoning, statistics and knowledge management) in an e?ort to help people gain insight, und- stand and interpret large quantities of (usually) semi-structured and unstr- tured data. Despite the advances made during the last few years, many issues remain unresolved. Proper co-ordination activities, dissemination of current trends and standardisation of the procedures have been identi?ed, as key needs. There are many questions still unanswered, especially to the potential users; what is the scope of Text Mining, who uses it and for what purpose, what constitutes the leading trends in the ?eld of Text Mining - especially in relation to IT - and whether there still remain areas to be covered. Knowledge Mining draws upon many of the key concepts of knowledge management, data mining and knowledge discovery, meta-analysis and data visualization. Within the context of scienti?c research, knowledge mining is principally concerned with the quantitative synthesis and visualization of - search results and ?ndings. The results of knowledge mining are increased scienti?c understanding along with improvements in research quality and value. Knowledge mining products can be used to highlight research opportunities, assist with the p- sentation of "best" scienti?c evidence, facilitate research portfolio mana- ment, as well as, facilitate policy setting and decision making.

The world of text mining is simultaneously a minefield and a gold mine. It is an exciting application field and an area of scientific research that is currently under rapid development. It uses techniques from well-established scientific fields (e.g. data mining, machine learning, information retrieval, natural language processing, case based reasoning, statistics and knowledge management) in an effort to help people gain insight, understand and interpret large quantities of (usually) semi-structured and unstructured data. Despite the advances made during the last few years, many issues remain umesolved. Proper co-ordination activities, dissemination of current trends and standardisation of the procedures have been identified, as key needs. There are many questions still unanswered, especially to the potential users; what is the scope of Text Mining, who uses it and for what purpose, what constitutes the leading trends in the field of Text Mining -especially in relation to IT- and whether there still remain areas to be covered."

Web Personalization can be de?ned as any set of actions that can tailor the Webexperiencetoaparticularuserorsetofusers. Toachievee?ectivepers- alization, organizationsmustrelyonallavailabledata, includingtheusageand click-stream data (re?ecting user behaviour), the site content, the site str- ture, domainknowledge, aswellasuserdemographicsandpro?les. Inaddition, e?cient and intelligent techniques are needed to mine this data for actionable knowledge, and to e?ectively use the discovered knowledge to enhance the users' Web experience. These techniques must address important challenges emanating from the size and the heterogeneous nature of the data itself, as wellasthedynamicnatureofuserinteractionswiththeWeb. Thesechallenges include the scalability of the personalization solutions, data integration, and successful integration of techniques from machine learning, information - trievaland?ltering, databases, agentarchitectures, knowledgerepresentation, data mining, text mining, statistics, user modelling and human-computer - teraction. The Semantic Web adds one more dimension to this. The workshop will focus on the semantic web approach to personalization and adaptation. The Web has been formed to be an integral part of numerous applications inwhichauserinteractswithaserviceprovider, productsellers, governmental organisations, friends and colleagues. Content and services are available at di?erent sources and places. Hence, Web applications need to combine all available knowledge in order to form personalized, user-friendly, and busine- optimal servi

In recent years, the use of Artificial Intelligence (AI) techniques has been greatly increased. The term "intelligence" seems to be a "must" in a large number of European and International project calls. AI Techniques have been used in almost any domain. Application-oriented systems usually incorporate some kind of "intelligence" by using techniques stemming from intelligent search, knowledge representation, machine learning, knowledge discovery, intelligent agents, computational intelligence etc. The Workshop on "Applications with Artificial Intelligence" seeks for quality papers on computer applications that incorporate some kind of AI technique. The objective of the workshop was to bring together scientists, engineers and practitioners, who work on designing or developing applications that use intelligent techniques or work on intelligent techniques and apply them to application domains (like medicine, biology, education etc), to present and discuss their research works and exchange ideas in this book.

Text mining is an exciting application ?eld and an area of scienti?c - search that is currently under rapid development. It uses techniques from well-established scienti?c ?elds (e. g. data mining, machine learning, infor- tion retrieval, natural language processing, case-based reasoning, statistics and knowledge management) in an e?ort to help people gain insight, und- stand and interpret large quantities of (usually) semi-structured and unstr- tured data. Despite the advances made during the last few years, many issues remain unresolved. Proper co-ordination activities, dissemination of current trends and standardisation of the procedures have been identi?ed, as key needs. There are many questions still unanswered, especially to the potential users; what is the scope of Text Mining, who uses it and for what purpose, what constitutes the leading trends in the ?eld of Text Mining - especially in relation to IT - and whether there still remain areas to be covered. Knowledge Mining draws upon many of the key concepts of knowledge management, data mining and knowledge discovery, meta-analysis and data visualization. Within the context of scienti?c research, knowledge mining is principally concerned with the quantitative synthesis and visualization of - search results and ?ndings. The results of knowledge mining are increased scienti?c understanding along with improvements in research quality and value. Knowledge mining products can be used to highlight research opportunities, assist with the p- sentation of "best" scienti?c evidence, facilitate research portfolio mana- ment, as well as, facilitate policy setting and decision making.

Web Personalization can be de?ned as any set of actions that can tailor the Webexperiencetoaparticularuserorsetofusers. Toachievee?ectivepers- alization, organizationsmustrelyonallavailabledata, includingtheusageand click-stream data (re?ecting user behaviour), the site content, the site str- ture, domainknowledge, aswellasuserdemographicsandpro?les. Inaddition, e?cient and intelligent techniques are needed to mine this data for actionable knowledge, and to e?ectively use the discovered knowledge to enhance the users' Web experience. These techniques must address important challenges emanating from the size and the heterogeneous nature of the data itself, as wellasthedynamicnatureofuserinteractionswiththeWeb. Thesechallenges include the scalability of the personalization solutions, data integration, and successful integration of techniques from machine learning, information - trievaland?ltering, databases, agentarchitectures, knowledgerepresentation, data mining, text mining, statistics, user modelling and human-computer - teraction. The Semantic Web adds one more dimension to this. The workshop will focus on the semantic web approach to personalization and adaptation. The Web has been formed to be an integral part of numerous applications inwhichauserinteractswithaserviceprovider, productsellers, governmental organisations, friends and colleagues. Content and services are available at di?erent sources and places. Hence, Web applications need to combine all available knowledge in order to form personalized, user-friendly, and busine- optimal servi

In recent years, the use of Artificial Intelligence (AI) techniques has been greatly increased. The term "intelligence" seems to be a "must" in a large number of European and International project calls. AI Techniques have been used in almost any domain. Application-oriented systems usually incorporate some kind of "intelligence" by using techniques stemming from intelligent search, knowledge representation, machine learning, knowledge discovery, intelligent agents, computational intelligence etc. The Workshop on "Applications with Artificial Intelligence" seeks for quality papers on computer applications that incorporate some kind of AI technique. The objective of the workshop was to bring together scientists, engineers and practitioners, who work on designing or developing applications that use intelligent techniques or work on intelligent techniques and apply them to application domains (like medicine, biology, education etc), to present and discuss their research works and exchange ideas in this book.

The world of text mining is simultaneously a minefield and a gold mine. It is an exciting application field and an area of scientific research that is currently under rapid development. It uses techniques from well-established scientific fields (e.g. data mining, machine learning, information retrieval, natural language processing, case based reasoning, statistics and knowledge management) in an effort to help people gain insight, understand and interpret large quantities of (usually) semi-structured and unstructured data. Despite the advances made during the last few years, many issues remain umesolved. Proper co-ordination activities, dissemination of current trends and standardisation of the procedures have been identified, as key needs. There are many questions still unanswered, especially to the potential users; what is the scope of Text Mining, who uses it and for what purpose, what constitutes the leading trends in the field of Text Mining -especially in relation to IT- and whether there still remain areas to be covered."