Extensions of fuzzy measures and Sugeno integral for possibilistic truth values

Bronselaer, Antoon; Hallez, Axel; Tré, Guy De

doi:10.1002/int.20327

Cited by 8 publications

(9 citation statements)

References 7 publications

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“…The Sugeno integral introduced in [8] combines conditional necessity (γ T and γ F ) with marginal necessity (the PTVs obtained from atomic comparison) into one PTV that reflects the uncertainty about the fact that two complex objects are coreferent. The inference used for this combination is purely possibilistic in nature and is therefore a valid and well suited aggregation method for PTVs in the case of coreference.…”

Section: Evaluators For Complex Objectsmentioning

confidence: 99%

“…To obtain the overall uncertainty on the coreference of two POIs, the elementary evaluators are applied and their resulting possibilistic truth values are aggregated. For this aggregation, a variant of the Sugeno integral, as presented in [8] is used. The proposed merging approach for coreferent POIs uses the possibilistic truth values that are returned from the elementary evaluations and the aggregation, to determine how and which parts of two coreferent POIs should be merged to obtain a single deduplicated POI.…”

Section: Introductionmentioning

confidence: 99%

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Automated Cleansing of POI Databases

Tré

Britsom

Matthé

et al. 2013

Intelligent Systems Reference Library

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In the context of geographic information systems (GIS), points of interest (POIs) are descriptions that denote geographical locations which might be of interest for some user purposes. Examples are public transport facilities, historical buildings, hotels and restaurants, recreation areas, hospitals etc. Because information gathering with respect to POIs is usually resource consuming, the user community is often involved in this task. In general, POI data originate from different sources (or users) and are therefore vulnerable to imperfections which might have a negative impact on data quality. Different POIs referring to, or describing the same physical geographical location might exist. Such POIs are said to be coreferent POIs. Coreferent POIs must be avoided as they could harm the data(base) quality and integrity. In this chapter, a novel soft computing technique for the (semi-)automated cleansing of POI databases is proposed. The proposed technique consists of two consecutive main steps: the detection of collections of coreferent POIs and the fusion, for each collection, of all coreferent POIs into a single consistent POI that represents all the POIs in the collection. The technique is based on fuzzy set theory, whereas possibility theory is used to cope with the uncertainties in the data. It can be used as a component of (semi-)automated data quality improvement strategies for databases and other information sources.

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Section: Evaluators For Complex Objectsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Automated Cleansing of POI Databases

Tré

Britsom

Matthé

et al. 2013

Intelligent Systems Reference Library

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“…Aggregation of PTVs may be carried out using the Sugeno integral for possibilistic truth values as defined in [6]; cf. also [7].…”

Section: Definition 1 (Comparison Operator)mentioning

confidence: 99%

“…To this aim the aggregation of the PTVs expressing the paths coreference is done using a technique based on the Sugeno integral for PTVs [6], in a similar way as proposed for the 'Aggregation at the steps level' described in Step 2, Substep 4. As argued earlier, this approach makes it possible to adequately cope with the different importance of aggregated elements, paths in this case.…”

Section: ) Aggregation At the Steps Levelmentioning

confidence: 99%

Coreference detection in XML metadata

Szymczak

Zadrożny

Tré

2013

2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS)

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Abstract-Preserving data quality is an important issue in data collection management. One of the crucial issues hereby is the detection of duplicate objects (called coreferent objects) which describe the same entity, but in different ways. In this paper we present a method for detecting coreferent objects in metadata, in particular in XML schemas. Our approach consists in comparing the paths from a root element to a given element in the schema. Each path precisely defines the context and location of a specific element in the schema. Path matching is based on the comparison of the different steps of which paths are composed. The uncertainty about the matching of steps is expressed with possibilistic truth values and aggregated using the Sugeno integral. The discovered coreference of paths can help for determining the coreference of different XML schemas.

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“…Usually, relieving a database from its duplicate data requires two distinct steps: match and fuse. In the 'match' step [1,2,3,4], the basic problem is to compare two pieces of data (e.g., database records) and to decide whether they are duplicate or not. The goal of the 'match' step is thus to find all duplicate data in a database.…”

Section: Introductionmentioning

confidence: 99%

Weak Preservation of Multi-Valued Fusion

Bronselaer¹,

Tré²

2013

Proceedings of the 8th Conference of the European Society for Fuzzy Logic and Technology

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Fusion functions are important data integration tools that map a multiset of objects (i.e., the sources) onto a single object (i.e., the solution). Traditionally, it is assumed that the objects of interest are single-valued. In this paper, it will be assumed that each object has a multi-valued data structure, leading to a framework of second order fusion functions. An important class of such functions is called preservative and is characterized by the fact that one of the input objects is returned. A disadvantage of these functions is the a-priori limitation of the output space to the input objects. It is investigated here how this disadvantage can be mitigated by studying the principle of weak-preservation. The main idea is hereby that, instead of preserving one of the sources, a characteristic feature of one of the sources is preserved. Three such features will be studied: cardinality, k-cut and multiplicity distribution. It will then be shown how weak-preservation can be utilized in the design of second order fusion functions.

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Extensions of fuzzy measures and Sugeno integral for possibilistic truth values

Cited by 8 publications

References 7 publications

Automated Cleansing of POI Databases

Automated Cleansing of POI Databases

Coreference detection in XML metadata

Weak Preservation of Multi-Valued Fusion

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