Leveraging personal metadata for Desktop search: The Beagle++ system

Minack, Enrico; Paiu, Raluca; Costache, Stefania; Demartini, Gianluca; Gaugaz, Julien; Ioannou, Ekaterini; Chirita, Paul-Alexandru; Nejdl, Wolfgang

doi:10.1016/j.websem.2009.12.001

Cited by 13 publications

(4 citation statements)

References 28 publications

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“…As a desktop search engine, Beagle++ utilizes a combination of indexed and structured search [30]. Wang et al [48] propose a graph-based learning approach with multiple features for web image search.…”

Section: Structured Mmirmentioning

confidence: 99%

A faceted approach to reachability analysis of graph modelled collections

Sabetghadam

Lupu

Bierig

et al. 2017

Int J Multimed Info Retr

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Nowadays, there is a proliferation of available information sources from different modalities-text, images, audio, video and more. Information objects are not isolated anymore. They are frequently connected via metadata, semantic links, etc. This leads to various challenges in graph-based information retrieval. This paper is concerned with the reachability analysis of multimodal graph modelled collections. We use our framework to leverage the combination of features of different modalities through our formulation of faceted search. This study highlights the effect of different facets and link types in improving reachability of relevant information objects. The experiments are performed on the Image CLEF 2011 Wikipedia collection with about 400,000 documents and images. The results demonstrate that the combination of different facets is conductive to obtain higher reachability. We obtain 373% recall gain for very hard topics by using our graph model of the collection. Further, by adding semantic links to the collection, we gain a 10% increase in the overall recall.

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Section: Structured Mmirmentioning

confidence: 99%

A faceted approach to reachability analysis of graph modelled collections

Sabetghadam

Lupu

Bierig

et al. 2017

Int J Multimed Info Retr

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“…Minack et al [24] evaluated image-related metadata based search on personal image collections. Liu et al [22] proposed a feature combination method to classify digital images that combined image content and EXIF metadata based on linear-discriminant-analysis (LDA) for digital photograph management.…”

Section: Metadata For Grouping Filesmentioning

confidence: 99%

Eliciting file relationships using metadata based associations for digital forensics

Raghavan¹

2014

CSIT

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In the conventional system of analysis that is concerned with digital forensics, content is analyzed to describe the state of files in digital evidence and ascertain their relevance. Such content analysis is carried out using ''searching''. When searching a file or for a file, use of keywords is the norm. When the exact words are not known, one may use regular expression search which uses a more flexible language for describing a set of keywords that fit a pattern. During analysis, there is also a need to identify all types of associations that exist between the files to answer the six fundamental questions of what, when, where, how, who and why. If the keywords and pattern have limited scope, an examiner often has very little to go on. Metadata contains information that represents the state of a file, even if partially. Besides, metadata based search is amenable to automation by virtue of the ubiquitous nature of metadata. During analysis, metadata can be used to ascertain the nature of digital photographs that were processed using software and identify digitally generated images that resemble original photographs. Metadata can also be used to identify word processing documents that were derived from other documents and stored as a duplicate or after modification in such a way that traditional techniques cannot detect. Often what is needed is the ability to identify section(s) of the evidence where relevant information appears to reside. Metadata based matches give rise to file relationships that encapsulate the event sequence among related files aiding in the discovery. This paper proposes a method to automatically identify associations among the files in digital evidence at the syntactic and semantic levels using metadata. We apply this method to identify metadata associations from collections of image files and word processing documents and elicit inter-file relationships for the purpose of identifying interesting or relevant files from large file collections in digital evidence. We demonstrate that the file relationships identified using metadata help in the identification of doctored photographs and copied documents.

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“…Shopping services, travel data from various travel web sites, and movies [45] extracted mainly from IMDB 5 . Another interesting kind of scenarios [57] is those derived from Personal Information Management (PIM) systems. There are examples with data describing up to 3,000 people [29,46].…”

Section: [Static Datasets]mentioning

confidence: 99%

On Generating Benchmark Data for Entity Matching

2012

Self Cite

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Entity matching has been a fundamental task in every major integration and data cleaning effort. It aims at identifying whether two different pieces of information are referring to the same real world object. It can also form the basis of entity search by finding the entities in a repository that best match a user specification. Despite the many different entity matching techniques that have been developed over time, there is still no widely accepted benchmark for evaluating and comparing them. This paper introduces EMBench, a principled system for the evaluation of entity matching systems. In contrast to existing similar efforts, EMBench offers a unique test case generation approach that combines different levels of types, complexity, and scales, allowing a complete and accurate evaluation of the different aspects of a matching system. After presenting the basic principles of EMBench and its functionality, a comprehensive evaluation is performed on some existing matching systems that showcases its discriminative power in highlighting their capabilities and limitations. EMBench has all the characteristics of a benchmark and can serve as a standard evaluation methodology provided that it gains popularity and wide acceptance.

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Leveraging personal metadata for Desktop search: The Beagle++ system

Cited by 13 publications

References 28 publications

A faceted approach to reachability analysis of graph modelled collections

A faceted approach to reachability analysis of graph modelled collections

Eliciting file relationships using metadata based associations for digital forensics

On Generating Benchmark Data for Entity Matching

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