Constraining the Search Space in Temporal Pattern Mining

Agents in dynamic environments have to deal with complex situations including various temporal interrelations of actions and events. Discovering frequent patterns in such scenes can be useful in order to create prediction rules which can be used to predict future activities or situations. We present the algorithm MiTemP which learns frequent patterns based on a time intervalbased relational representation. Additionally the problem has also been transfered to a pure relational association rule mining task which can be handled by WARMR. The two approaches are compared in a number of experiments. The experiments show the advantage of avoiding the creation of impossible or redundant patterns with MiTemP. While less patterns have to be explored on average with MiTemP more frequent patterns are found at an earlier refinement level

Optimality in Goal-Dependent Analysis of Sharing

We face the problems of correctness, optimality and precision for the static analysis of logic programs, using the theory of abstract interpretation. We propose a framework with a denotational, goal-dependent semantics equipped with two unification operators for forward unification (calling a procedure) and backward unification (returning from a procedure). The latter is implemented through a matching operation. Our proposal clarifies and unifies many different frameworks and ideas on static analysis of logic programming in a single, formal setting. On the abstract side, we focus on the domain Sharing by Jacobs and Langen and provide the best correct approximation of all the primitive semantic operators, namely, projection, renaming, forward and backward unification. We show that the abstract unification operators are strictly more precise than those in the literature defined over the same abstract domain. In some cases, our operators are more precise than those developed for more complex domains involving linearity and freeness. To appear in Theory and Practice of Logic Programming (TPLP

Four Lessons in Versatility or How Query Languages Adapt to the Web

Exposing not only human-centered information, but machine-processable data on the Web is one of the commonalities of recent Web trends. It has enabled a new kind of applications and businesses where the data is used in ways not foreseen by the data providers. Yet this exposition has fractured the Web into islands of data, each in different Web formats: Some providers choose XML, others RDF, again others JSON or OWL, for their data, even in similar domains. This fracturing stifles innovation as application builders have to cope not only with one Web stack (e.g., XML technology) but with several ones, each of considerable complexity. With Xcerpt we have developed a rule- and pattern based query language that aims to give shield application builders from much of this complexity: In a single query language XML and RDF data can be accessed, processed, combined, and re-published. Though the need for combined access to XML and RDF data has been recognized in previous work (including the W3C’s GRDDL), our approach differs in four main aspects: (1) We provide a single language (rather than two separate or embedded languages), thus minimizing the conceptual overhead of dealing with disparate data formats. (2) Both the declarative (logic-based) and the operational semantics are unified in that they apply for querying XML and RDF in the same way. (3) We show that the resulting query language can be implemented reusing traditional database technology, if desirable. Nevertheless, we also give a unified evaluation approach based on interval labelings of graphs that is at least as fast as existing approaches for tree-shaped XML data, yet provides linear time and space querying also for many RDF graphs. We believe that Web query languages are the right tool for declarative data access in Web applications and that Xcerpt is a significant step towards a more convenient, yet highly efficient data access in a “Web of Data”

Employment Stability of Entrants in Newly Founded Firms: A Matching Approach Using Linked Employer-Employee Data from Germany

Using a linked employer-employee dataset and taking the perspective of individuals rather than firms, this paper analyzes some effects of joining start-ups. We show that entrants in new firms differ from those joining incumbent firms, and we use a matching approach to compare a group of employees joining new firms in 1995/96 with a control group entering incumbent firms. Our results indicate that individuals’ employment stability was higher in incumbent than in newly founded firms while their risk of becoming unemployed was lower. In particular in eastern Germany, joining firms that were older than six years was the best strategy.linked employer-employee data, newly founded firms, unemployment, employment, Germany

Employment stability of entrants in newly founded firms: a matching approach using linked employer-employee data from Germany

Using a linked employer-employee dataset and taking the perspective of individuals rather than firms, this paper analyzes some effects of joining start-ups. We show that entrants in new firms differ from those joining incumbent firms, and we use a matching approach to compare a group of employees joining new firms in 1995/96 with a control group entering incumbent firms. Our results indicate that individuals' employment stability was higher in incumbent than in newly founded firms while their risk of becoming unemployed was lower. In particular in eastern Germany, joining firms that were older than six years was the best strategy. -- Diese Arbeit analysiert unter Verwendung eines verbundenen Arbeitgeber-Arbeitnehmer-Datensatzes einige Auswirkungen des Eintritts in Neugründungen, wobei die Sicht von Individuen statt von Firmen eingenommen wird. Wir zeigen, dass Personen, die in neue Firmen eintreten, sich von Eintreten-den in bestehende Firmen unterscheiden, und wir verwenden einen Matching-Ansatz, um eine Gruppe von Personen, die 1995/96 in Neugründungen eintrat, mit einer Kontrollgruppe von Eintretenden in bestehende Firmen zu vergleichen. Unsere Ergebnisse deuten darauf hin, dass die Beschäftigungsstabilität der eintre-tenden Personen in bestehenden Firmen höher als in Neugründungen ausfiel, während ihr Risiko arbeitslos zu werden geringer war. Insbesondere in den neuen Bundesländern bestand die beste Strategie darin, in Firmen einzutreten, die älter als sechs Jahre waren.employment,unemployment,newly founded firma,linked employer-employee data,Germany

Employment stability of entrants in newly founded firms : a matching approach using linked employer-employee data from Germany

"Using a linked employer-employee dataset and taking the perspective of individuals rather than firms, this paper analyzes some effects of joining start-ups. We show that entrants in new firms differ from those joining incumbent firms, and we use a matching approach to compare a group of employees joining new firms in 1995/96 with a control group entering incumbent firms. Our results indicate that individuals' employment stability was higher in incumbent than in newly founded firms while their risk of becoming unemployed was lower. In particular in eastern Germany, joining firms that were older than six years was the best strategy." (Author's abstract, IAB-Doku) ((en))Unternehmen, Arbeitskräfte, berufliche Qualifikation, Betriebszugehörigkeit - Dauer, Beschäftigungsdauer, Arbeitslosigkeit, Berufsverlauf, zwischenbetriebliche Mobilität, Arbeitsplatzwechsel, Arbeitskräftemobilität