D2. 2.4: Alignment implementation and benchmarking results

2007

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KnowledgeWeb deliverable D, 2004

Definition of a common semantic framework for characterizing alignment of heterogeneous information.

Knowledge Web NoE (FP6-507482), 2007

This deliverable provides the description of an alignment language which is both expressive and independent from ontology languages. It defines the language through its abstract syntax and semantics depending on ontology language semantics. It then describes two concrete syntax: an exchange syntax in RDF/XML and a surface syntax for human consumption. Finally, it presents the current implementation of this expressive language within the Alignment API taking advantage of the OMWG implementation.

1998

This paper describes the work achieved in the first half of a 4-year cooperative research project (ARCADE), financed by AUPELF-UREF. The project is devoted to the evaluation of parallel text alignment techniques. In its first period ARCADE ran a competition between six systems on a sentence-to-sentence alignment task which yielded two main types of results. First, a large reference bilingual corpus comprising of texts of different genres was created, each presenting various degrees of difficulty with respect to the alignment task. Second, significant methodological progress was made both on the evaluation protocols and metrics, and the algoritbm.q used by the different systems. For the second phase, which is now underway, ARCADE has been opened to a larger number of teams who will tackle the problem of word-level alignment.

Kweb deliverable: D

Definition of a common framework for characterizing alignment of heterogeneous information. This report describes various approaches towards this goal and shows the relations between them. It also provides a description of the alignment sructure and process.

Knowledge Web NoE, 2007

This deliverable provides the description of an alignment language which is both expressive and independent from ontology languages. It defines the language through its abstract syntax and semantics depending on ontology language semantics. It then describes two concrete syntax: an exchange syntax in RDF/XML and a surface syntax for human consumption. Finally, it presents the current implementation of this expressive language within the Alignment API taking advantage of the OMWG implementation.

2017

Conformance checking aims at assessing whether a process model and event data, recorded in an event log, conform to each other. In recent years, alignments have proven extremely useful for calculating conformance statistics. Computing optimal alignments is equivalent to solving a shortest path problem on the state space of the synchronous product net of a given Petri net and event data. State-of-the-art alignmentbased conformance checking implementations exploit the A∗-algorithm, a heuristic search method for shortest path problems, and include a wide range of parameters that likely influence their performance. In this paper, we present an exploratory empirical evaluation of parametrization of the A∗-algorithm used in alignment computation. Our initial results show that the performance of alignment computation greatly depends on adequate parametrization of the underlying search algorithm.

2005

Among the variety of alignment approaches (e.g., using machine learning, subsumption computation, formal concept analysis, etc.) similarity-based ones rely on a quantitative assessment of pair-wise likeness between entities. Our own alignment tool, OLA, features a similarity model rooted in principles such as: completeness on the ontology language features, weighting of different feature contributions and mutual influence between related ontology entities. The resulting similarities are recursively defined hence their values are calculated by a step-wise, fixed-point-bound approximation process. For the OAEI 2005 contest, OLA was provided with an additional mechanism for weight determination that increases the autonomy of the system.

The 7th International …, 2008

TaxoMap is an alignment tool which aim is to discover rich correspondences between concepts. It performs an oriented alignment (from a source to a target ontology) and takes into account labels and sub-class descriptions. Our participation in last year edition of the competition have put the emphasis on certain limits. TaxoMap 2 is a new implementation of TaxoMap that reduces significantly runtime and enables parameterization by specifying the ontology language and different thresholds used to extract different mapping relations. The new implementation stresses on terminological techniques, it takes into account synonymy, and multi-label description of concepts. Special effort was made to handle large-scale ontologies by partitioning input ontologies into modules to align. We conclude the paper by pointing out the necessary improvements that need to be made.

This paper presents our first participation in the OAEI 2007 campaign. It describes an approach to align taxonomies which relies on terminological and structural techniques applied sequentially. We performed our method with various taxonomies using our prototype, Tax-oMap. Previous experimental results were encouraging and demonstrate the relevance of this alignment approach. In this paper, we evaluate the strengths and weaknesses of TaxoMap in the context of the OAEI campaign where the ontologies to align are different from taxonomies we are used to deal with.