Mining Redescriptions with Siren Article Swipe
Esther Galbrun
,
Pauli Miettinen
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1145/3007212
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1145/3007212
In many areas of science, scientists need to find distinct common characterizations of the same objects and, vice versa, to identify sets of objects that admit multiple shared descriptions. For example, in biology, an important task is to identify the bioclimatic constraints that allow some species to survive, that is, to describe geographical regions both in terms of the fauna that inhabits them and of their bioclimatic conditions. In data analysis, the task of automatically generating such alternative characterizations is called redescription mining. If a domain expert wants to use redescription mining in his research, merely being able to find redescriptions is not enough. He must also be able to understand the redescriptions found, adjust them to better match his domain knowledge, test alternative hypotheses with them, and guide the mining process toward results he considers interesting. To facilitate these goals, we introduce Siren, an interactive tool for mining and visualizing redescriptions. Siren allows to obtain redescriptions in an anytime fashion through efficient, distributed mining, to examine the results in various linked visualizations, to interact with the results either directly or via the visualizations, and to guide the mining algorithm toward specific redescriptions. In this article, we explain the features of Siren and why they are useful for redescription mining. We also propose two novel redescription mining algorithms that improve the generalizability of the results compared to the existing ones.
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Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1145/3007212
- OA Status
- green
- Cited By
- 7
- References
- 50
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2586143265
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2586143265Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1145/3007212Digital Object Identifier
- Title
-
Mining Redescriptions with SirenWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2018Year of publication
- Publication date
-
2018-01-31Full publication date if available
- Authors
-
Esther Galbrun, Pauli MiettinenList of authors in order
- Landing page
-
https://doi.org/10.1145/3007212Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://hal.science/hal-01399213Direct OA link when available
- Concepts
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Siren (mythology), Computer science, Task (project management), Generalizability theory, Domain (mathematical analysis), Data mining, Visualization, Data science, Mathematics, Statistics, Management, Mathematical analysis, Literature, Art, EconomicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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7Total citation count in OpenAlex
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2025: 1, 2024: 2, 2023: 2, 2021: 1, 2018: 1Per-year citation counts (last 5 years)
- References (count)
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50Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.such | 76 |
| abstract_inverted_index.task | 35, 72 |
| abstract_inverted_index.test | 122 |
| abstract_inverted_index.that | 24, 42, 48, 60, 218 |
| abstract_inverted_index.them | 62, 115 |
| abstract_inverted_index.they | 204 |
| abstract_inverted_index.this | 194 |
| abstract_inverted_index.tool | 146 |
| abstract_inverted_index.vice | 17 |
| abstract_inverted_index.with | 125, 175 |
| abstract_inverted_index.Siren | 152, 201 |
| abstract_inverted_index.admit | 25 |
| abstract_inverted_index.allow | 43 |
| abstract_inverted_index.areas | 2 |
| abstract_inverted_index.being | 96 |
| abstract_inverted_index.fauna | 59 |
| abstract_inverted_index.guide | 128, 186 |
| abstract_inverted_index.match | 118 |
| abstract_inverted_index.novel | 214 |
| abstract_inverted_index.ones. | 229 |
| abstract_inverted_index.terms | 56 |
| abstract_inverted_index.their | 65 |
| abstract_inverted_index.them, | 126 |
| abstract_inverted_index.these | 139 |
| abstract_inverted_index.wants | 87 |
| abstract_inverted_index.Siren, | 143 |
| abstract_inverted_index.adjust | 114 |
| abstract_inverted_index.allows | 153 |
| abstract_inverted_index.better | 117 |
| abstract_inverted_index.called | 80 |
| abstract_inverted_index.common | 10 |
| abstract_inverted_index.domain | 85, 120 |
| abstract_inverted_index.either | 178 |
| abstract_inverted_index.expert | 86 |
| abstract_inverted_index.found, | 113 |
| abstract_inverted_index.goals, | 140 |
| abstract_inverted_index.linked | 171 |
| abstract_inverted_index.merely | 95 |
| abstract_inverted_index.mining | 91, 130, 148, 188, 216 |
| abstract_inverted_index.obtain | 155 |
| abstract_inverted_index.shared | 27 |
| abstract_inverted_index.toward | 132, 190 |
| abstract_inverted_index.useful | 206 |
| abstract_inverted_index.versa, | 18 |
| abstract_inverted_index.anytime | 159 |
| abstract_inverted_index.enough. | 103 |
| abstract_inverted_index.examine | 166 |
| abstract_inverted_index.explain | 197 |
| abstract_inverted_index.fashion | 160 |
| abstract_inverted_index.improve | 219 |
| abstract_inverted_index.mining, | 164 |
| abstract_inverted_index.mining. | 82, 209 |
| abstract_inverted_index.objects | 15, 23 |
| abstract_inverted_index.process | 131 |
| abstract_inverted_index.propose | 212 |
| abstract_inverted_index.regions | 53 |
| abstract_inverted_index.results | 133, 168, 177, 224 |
| abstract_inverted_index.species | 45 |
| abstract_inverted_index.through | 161 |
| abstract_inverted_index.various | 170 |
| abstract_inverted_index.article, | 195 |
| abstract_inverted_index.biology, | 32 |
| abstract_inverted_index.compared | 225 |
| abstract_inverted_index.describe | 51 |
| abstract_inverted_index.directly | 179 |
| abstract_inverted_index.distinct | 9 |
| abstract_inverted_index.example, | 30 |
| abstract_inverted_index.existing | 228 |
| abstract_inverted_index.features | 199 |
| abstract_inverted_index.identify | 20, 38 |
| abstract_inverted_index.inhabits | 61 |
| abstract_inverted_index.interact | 174 |
| abstract_inverted_index.multiple | 26 |
| abstract_inverted_index.science, | 4 |
| abstract_inverted_index.specific | 191 |
| abstract_inverted_index.survive, | 47 |
| abstract_inverted_index.algorithm | 189 |
| abstract_inverted_index.analysis, | 70 |
| abstract_inverted_index.considers | 135 |
| abstract_inverted_index.important | 34 |
| abstract_inverted_index.introduce | 142 |
| abstract_inverted_index.research, | 94 |
| abstract_inverted_index.algorithms | 217 |
| abstract_inverted_index.efficient, | 162 |
| abstract_inverted_index.facilitate | 138 |
| abstract_inverted_index.generating | 75 |
| abstract_inverted_index.hypotheses | 124 |
| abstract_inverted_index.knowledge, | 121 |
| abstract_inverted_index.scientists | 5 |
| abstract_inverted_index.understand | 110 |
| abstract_inverted_index.alternative | 77, 123 |
| abstract_inverted_index.bioclimatic | 40, 66 |
| abstract_inverted_index.conditions. | 67 |
| abstract_inverted_index.constraints | 41 |
| abstract_inverted_index.distributed | 163 |
| abstract_inverted_index.interactive | 145 |
| abstract_inverted_index.visualizing | 150 |
| abstract_inverted_index.geographical | 52 |
| abstract_inverted_index.interesting. | 136 |
| abstract_inverted_index.automatically | 74 |
| abstract_inverted_index.descriptions. | 28 |
| abstract_inverted_index.redescription | 81, 90, 208, 215 |
| abstract_inverted_index.redescriptions | 100, 112, 156 |
| abstract_inverted_index.redescriptions. | 151, 192 |
| abstract_inverted_index.visualizations, | 172, 183 |
| abstract_inverted_index.generalizability | 221 |
| abstract_inverted_index.characterizations | 11, 78 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 2 |
| citation_normalized_percentile.value | 0.52745504 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |