... Detlev Buland and Dietmar Seipel ... d-tree T(U,F)=(V,E,attr,dec) and a node WEV, dec(w)=Y-&a... more ... Detlev Buland and Dietmar Seipel ... d-tree T(U,F)=(V,E,attr,dec) and a node WEV, dec(w)=Y->B. Y->B is called a-violating functional dependency , iff it exists a node VEV with the following properties - w is in the subtree of v and v # w, - [dec(v)=X->A ar& Z:=Xnattr(w)] j [BeZ and Z p ...
Symposium on Languages, Applications and Technologies, 2021
We are proposing a keyword-based query interface for knowledge bases-including relational or dedu... more We are proposing a keyword-based query interface for knowledge bases-including relational or deductive databases-based on contextual background knowledge such as suitable join conditions or synonyms. Join conditions could be extracted from existing referential integrity (foreign key) constaints of the database schema. They could also be learned from other, previous database queries, if the database schema does not contain foreign key constraints. Given a textual representation-a word list-of a query to a relational database, one may parse the list into a structured term. The intelligent and cooperative part of our approach is to hypothesize the semantics of the word list and to find suitable links between the concepts mentioned in the query using contextual knowledge, more precisely join conditions between the database tables. We use a knowledge-based parser based on an extension of Definite Clause Grammars (Dcg) that are interweaved with calls to the database schema to suitably annotate the tokens as table names, table attributes, attribute values or relationships linking tables. Our tool DdQl yields the possible queries in a special domain specific rule language that extends Datalog, from which the user can choose one.
Link prediction is challenging, especially based on (scarce) historic data or in cold start scena... more Link prediction is challenging, especially based on (scarce) historic data or in cold start scenarios. In this paper, we show how to apply answer set programming (ASP) for formalizing link prediction in feature-rich networks, that is – in particular – using domain knowledge for network (and graph) analysis. We show, that applying ASP for link prediction provides a powerful declarative approach, as exemplified using simple predictors, and demonstrate according explanation generation using ASP. We present the application of the proposed methodological approach for explicative link prediction and analysis with explanation generation using different datasets. Keywords. Explainable AI, social network analysis, link prediction, answer set programming, Prolog, domain knowledge
< p> This volume constitutes the thoroughly refereed post-conference proceedings of... more < p> This volume constitutes the thoroughly refereed post-conference proceedings of the 17th International Conference on Applications of Declarative Programming and Knowledge Management, INAP 2007, and the 21st Workshop on Logic Programming, WLP 2007, held ...
Abstract The integration of concepts from logic and deduction into databases and knowledge bases ... more Abstract The integration of concepts from logic and deduction into databases and knowledge bases has created the field of deductive databases. Logic programming provides a powerful declarative language for accessing and maintaining knowledge in databases. Techniques from relational databases and automated deduction are useful for achieving efficient retrieval and reasoning in large knowledge bases. Thus, deductive databases can be used for building intelligent information systems. The contributions in this Proceedings ...
The use of general descriptive names, registered names, trademarks, service marks, etc. in this p... more The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.
Constraint Handling Rules (CHR) is usually compiled to logic programming languages. While there a... more Constraint Handling Rules (CHR) is usually compiled to logic programming languages. While there are implementations for imperative programming languages such as C and Java, its most popular host language remains Prolog. In this paper, we present Chr.js, a CHR system implemented in JavaScript, that is suitable for both the server-side and interactive client-side web applications. Chr.js provides (i) an interpreter, which is based on the asynchronous execution model of JavaScript, and (ii) an ahead-of-time compiler, resulting in synchronous constraint solvers with better performances. Because of the great popularity of JavaScript, Chr.js is the first CHR system that runs on almost all and even mobile devices, without the need for an additional runtime environment. As an example application we present the Chr.js Playground, an offline-capable web-interface which allows the interactive exploration of CHRs in every modern browser.
The integration of a rule representation in ontology languages enhances the developer's abilities... more The integration of a rule representation in ontology languages enhances the developer's abilities in the expression of knowledge. Likewise the integration creates new challenges for the design process of these knowledge bases. Thus, evaluation approaches have to cope with the merged methods. We introduce extensions to existing verification techniques to support the implementation of ontologies with rule enhancements, and we focus on the detection of anomalies that can especially occur due to the combined use of rules and ontological definitions.
The explication and the generation of explanations are prominent topics in artificial intelligenc... more The explication and the generation of explanations are prominent topics in artificial intelligence and data science, in order to make methods and systems more transparent and understandable for humans. This paper investigates the problem of link analysis, specifically link prediction and anomalous link discovery in social networks using the declarative method of Answer set programming (ASP). Applying ASP for link prediction provides a powerful declarative approach, e. g., for incorporating domain knowledge for explicative prediction. In this context, we propose a novel method for generating explanations-as offline justifications-using declarative program transformations. The method itself is purely based on syntactic transformations of declarative programs, e. g., in an ASP formalism, using rule instrumentation. We demonstrate the efficacy of the proposed approach, exemplifying it in an application on link analysis in social networks, also including domain knowledge.
The concept of association rules is well-known in data mining. But often redundancy and subsumpti... more The concept of association rules is well-known in data mining. But often redundancy and subsumption are not considered, and standard approaches produce thousands or even millions of resulting association rules. Without further information or post-mining approaches, this huge number of rules is typically useless for the domain specialistwhich is an instance of the infamous pattern explosion problem. In this work, we present a new definition of redundancy and subsumption based on the confidence and the support of the rules and propose postmining to prune a set of association rules. In a case study, we apply our method to association rules mined from spatio-temporal data. The data represent the trajectories of the ball in tennis matches-more precisely, the points/times the tennis ball hits the ground. The goal is to analyze the strategies of the players and to try to improve their performance by looking at the resulting association rules. The proposed approach is general, and can also be applied to other spatio-temporal data with a similar structure.
... Detlev Buland and Dietmar Seipel ... d-tree T(U,F)=(V,E,attr,dec) and a node WEV, dec(w)=Y-&a... more ... Detlev Buland and Dietmar Seipel ... d-tree T(U,F)=(V,E,attr,dec) and a node WEV, dec(w)=Y->B. Y->B is called a-violating functional dependency , iff it exists a node VEV with the following properties - w is in the subtree of v and v # w, - [dec(v)=X->A ar& Z:=Xnattr(w)] j [BeZ and Z p ...
Symposium on Languages, Applications and Technologies, 2021
We are proposing a keyword-based query interface for knowledge bases-including relational or dedu... more We are proposing a keyword-based query interface for knowledge bases-including relational or deductive databases-based on contextual background knowledge such as suitable join conditions or synonyms. Join conditions could be extracted from existing referential integrity (foreign key) constaints of the database schema. They could also be learned from other, previous database queries, if the database schema does not contain foreign key constraints. Given a textual representation-a word list-of a query to a relational database, one may parse the list into a structured term. The intelligent and cooperative part of our approach is to hypothesize the semantics of the word list and to find suitable links between the concepts mentioned in the query using contextual knowledge, more precisely join conditions between the database tables. We use a knowledge-based parser based on an extension of Definite Clause Grammars (Dcg) that are interweaved with calls to the database schema to suitably annotate the tokens as table names, table attributes, attribute values or relationships linking tables. Our tool DdQl yields the possible queries in a special domain specific rule language that extends Datalog, from which the user can choose one.
Link prediction is challenging, especially based on (scarce) historic data or in cold start scena... more Link prediction is challenging, especially based on (scarce) historic data or in cold start scenarios. In this paper, we show how to apply answer set programming (ASP) for formalizing link prediction in feature-rich networks, that is – in particular – using domain knowledge for network (and graph) analysis. We show, that applying ASP for link prediction provides a powerful declarative approach, as exemplified using simple predictors, and demonstrate according explanation generation using ASP. We present the application of the proposed methodological approach for explicative link prediction and analysis with explanation generation using different datasets. Keywords. Explainable AI, social network analysis, link prediction, answer set programming, Prolog, domain knowledge
< p> This volume constitutes the thoroughly refereed post-conference proceedings of... more < p> This volume constitutes the thoroughly refereed post-conference proceedings of the 17th International Conference on Applications of Declarative Programming and Knowledge Management, INAP 2007, and the 21st Workshop on Logic Programming, WLP 2007, held ...
Abstract The integration of concepts from logic and deduction into databases and knowledge bases ... more Abstract The integration of concepts from logic and deduction into databases and knowledge bases has created the field of deductive databases. Logic programming provides a powerful declarative language for accessing and maintaining knowledge in databases. Techniques from relational databases and automated deduction are useful for achieving efficient retrieval and reasoning in large knowledge bases. Thus, deductive databases can be used for building intelligent information systems. The contributions in this Proceedings ...
The use of general descriptive names, registered names, trademarks, service marks, etc. in this p... more The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.
Constraint Handling Rules (CHR) is usually compiled to logic programming languages. While there a... more Constraint Handling Rules (CHR) is usually compiled to logic programming languages. While there are implementations for imperative programming languages such as C and Java, its most popular host language remains Prolog. In this paper, we present Chr.js, a CHR system implemented in JavaScript, that is suitable for both the server-side and interactive client-side web applications. Chr.js provides (i) an interpreter, which is based on the asynchronous execution model of JavaScript, and (ii) an ahead-of-time compiler, resulting in synchronous constraint solvers with better performances. Because of the great popularity of JavaScript, Chr.js is the first CHR system that runs on almost all and even mobile devices, without the need for an additional runtime environment. As an example application we present the Chr.js Playground, an offline-capable web-interface which allows the interactive exploration of CHRs in every modern browser.
The integration of a rule representation in ontology languages enhances the developer's abilities... more The integration of a rule representation in ontology languages enhances the developer's abilities in the expression of knowledge. Likewise the integration creates new challenges for the design process of these knowledge bases. Thus, evaluation approaches have to cope with the merged methods. We introduce extensions to existing verification techniques to support the implementation of ontologies with rule enhancements, and we focus on the detection of anomalies that can especially occur due to the combined use of rules and ontological definitions.
The explication and the generation of explanations are prominent topics in artificial intelligenc... more The explication and the generation of explanations are prominent topics in artificial intelligence and data science, in order to make methods and systems more transparent and understandable for humans. This paper investigates the problem of link analysis, specifically link prediction and anomalous link discovery in social networks using the declarative method of Answer set programming (ASP). Applying ASP for link prediction provides a powerful declarative approach, e. g., for incorporating domain knowledge for explicative prediction. In this context, we propose a novel method for generating explanations-as offline justifications-using declarative program transformations. The method itself is purely based on syntactic transformations of declarative programs, e. g., in an ASP formalism, using rule instrumentation. We demonstrate the efficacy of the proposed approach, exemplifying it in an application on link analysis in social networks, also including domain knowledge.
The concept of association rules is well-known in data mining. But often redundancy and subsumpti... more The concept of association rules is well-known in data mining. But often redundancy and subsumption are not considered, and standard approaches produce thousands or even millions of resulting association rules. Without further information or post-mining approaches, this huge number of rules is typically useless for the domain specialistwhich is an instance of the infamous pattern explosion problem. In this work, we present a new definition of redundancy and subsumption based on the confidence and the support of the rules and propose postmining to prune a set of association rules. In a case study, we apply our method to association rules mined from spatio-temporal data. The data represent the trajectories of the ball in tennis matches-more precisely, the points/times the tennis ball hits the ground. The goal is to analyze the strategies of the players and to try to improve their performance by looking at the resulting association rules. The proposed approach is general, and can also be applied to other spatio-temporal data with a similar structure.
Uploads
Papers by Dietmar Seipel