Changes
On December 16, 2024 at 5:43:58 PM UTC, admin:
-
Changed value of field
doi_status
toTrue
in Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications -
Changed value of field
doi_date_published
to2024-12-16
in Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications -
Added resource Original Metadata to Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications
f | 1 | { | f | 1 | { |
2 | "access_rights": "", | 2 | "access_rights": "", | ||
3 | "author": "Haowen Xu", | 3 | "author": "Haowen Xu", | ||
4 | "author_email": "", | 4 | "author_email": "", | ||
5 | "citation": [], | 5 | "citation": [], | ||
6 | "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700", | 6 | "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700", | ||
7 | "defined_in": "https://doi.org/10.1145/3178876.3185996", | 7 | "defined_in": "https://doi.org/10.1145/3178876.3185996", | ||
8 | "doi": "10.57702/7u1wlqp5", | 8 | "doi": "10.57702/7u1wlqp5", | ||
n | 9 | "doi_date_published": null, | n | 9 | "doi_date_published": "2024-12-16", |
10 | "doi_publisher": "TIB", | 10 | "doi_publisher": "TIB", | ||
n | 11 | "doi_status": false, | n | 11 | "doi_status": true, |
12 | "domain": "https://service.tib.eu/ldmservice", | 12 | "domain": "https://service.tib.eu/ldmservice", | ||
13 | "extra_authors": [ | 13 | "extra_authors": [ | ||
14 | { | 14 | { | ||
15 | "extra_author": "Wenxiao Chen", | 15 | "extra_author": "Wenxiao Chen", | ||
16 | "orcid": "" | 16 | "orcid": "" | ||
17 | }, | 17 | }, | ||
18 | { | 18 | { | ||
19 | "extra_author": "Nengwen Zhao", | 19 | "extra_author": "Nengwen Zhao", | ||
20 | "orcid": "" | 20 | "orcid": "" | ||
21 | }, | 21 | }, | ||
22 | { | 22 | { | ||
23 | "extra_author": "Zeyan Li", | 23 | "extra_author": "Zeyan Li", | ||
24 | "orcid": "" | 24 | "orcid": "" | ||
25 | }, | 25 | }, | ||
26 | { | 26 | { | ||
27 | "extra_author": "Jiahao Bu", | 27 | "extra_author": "Jiahao Bu", | ||
28 | "orcid": "" | 28 | "orcid": "" | ||
29 | }, | 29 | }, | ||
30 | { | 30 | { | ||
31 | "extra_author": "Zhihan Li", | 31 | "extra_author": "Zhihan Li", | ||
32 | "orcid": "" | 32 | "orcid": "" | ||
33 | }, | 33 | }, | ||
34 | { | 34 | { | ||
35 | "extra_author": "Ying Liu", | 35 | "extra_author": "Ying Liu", | ||
36 | "orcid": "" | 36 | "orcid": "" | ||
37 | }, | 37 | }, | ||
38 | { | 38 | { | ||
39 | "extra_author": "Youjian Zhao", | 39 | "extra_author": "Youjian Zhao", | ||
40 | "orcid": "" | 40 | "orcid": "" | ||
41 | }, | 41 | }, | ||
42 | { | 42 | { | ||
43 | "extra_author": "Dan Pei", | 43 | "extra_author": "Dan Pei", | ||
44 | "orcid": "" | 44 | "orcid": "" | ||
45 | } | 45 | } | ||
46 | ], | 46 | ], | ||
47 | "groups": [ | 47 | "groups": [ | ||
48 | { | 48 | { | ||
49 | "description": "", | 49 | "description": "", | ||
50 | "display_name": "Anomaly Detection", | 50 | "display_name": "Anomaly Detection", | ||
51 | "id": "469caeeb-2eee-4858-a0f3-692b4da09dfe", | 51 | "id": "469caeeb-2eee-4858-a0f3-692b4da09dfe", | ||
52 | "image_display_url": "", | 52 | "image_display_url": "", | ||
53 | "name": "anomaly-detection", | 53 | "name": "anomaly-detection", | ||
54 | "title": "Anomaly Detection" | 54 | "title": "Anomaly Detection" | ||
55 | }, | 55 | }, | ||
56 | { | 56 | { | ||
57 | "description": "", | 57 | "description": "", | ||
58 | "display_name": "Time Series Analysis", | 58 | "display_name": "Time Series Analysis", | ||
59 | "id": "c0b2d680-8a2d-4a70-8cea-3de77e468832", | 59 | "id": "c0b2d680-8a2d-4a70-8cea-3de77e468832", | ||
60 | "image_display_url": "", | 60 | "image_display_url": "", | ||
61 | "name": "time-series-analysis", | 61 | "name": "time-series-analysis", | ||
62 | "title": "Time Series Analysis" | 62 | "title": "Time Series Analysis" | ||
63 | } | 63 | } | ||
64 | ], | 64 | ], | ||
65 | "id": "74265c60-b09f-47fe-9d34-23bcbb9ce452", | 65 | "id": "74265c60-b09f-47fe-9d34-23bcbb9ce452", | ||
66 | "isopen": false, | 66 | "isopen": false, | ||
67 | "landing_page": "https://doi.org/10.1145/3178876.3185996", | 67 | "landing_page": "https://doi.org/10.1145/3178876.3185996", | ||
68 | "license_title": null, | 68 | "license_title": null, | ||
69 | "link_orkg": "", | 69 | "link_orkg": "", | ||
70 | "metadata_created": "2024-12-16T17:43:56.738945", | 70 | "metadata_created": "2024-12-16T17:43:56.738945", | ||
n | 71 | "metadata_modified": "2024-12-16T17:43:56.738950", | n | 71 | "metadata_modified": "2024-12-16T17:43:57.113183", |
72 | "name": | 72 | "name": | ||
73 | n-via-variational-auto-encoder-for-seasonal-kpis-in-web-applications", | 73 | n-via-variational-auto-encoder-for-seasonal-kpis-in-web-applications", | ||
74 | "notes": "The authors used 18 well-maintained business KPIs from a | 74 | "notes": "The authors used 18 well-maintained business KPIs from a | ||
75 | large Internet company. All KPIs have an interval of 1 minute between | 75 | large Internet company. All KPIs have an interval of 1 minute between | ||
76 | two observations.", | 76 | two observations.", | ||
n | 77 | "num_resources": 0, | n | 77 | "num_resources": 1, |
78 | "num_tags": 3, | 78 | "num_tags": 3, | ||
79 | "organization": { | 79 | "organization": { | ||
80 | "approval_status": "approved", | 80 | "approval_status": "approved", | ||
81 | "created": "2024-11-25T12:11:38.292601", | 81 | "created": "2024-11-25T12:11:38.292601", | ||
82 | "description": "", | 82 | "description": "", | ||
83 | "id": "079d46db-32df-4b48-91f3-0a8bc8f69559", | 83 | "id": "079d46db-32df-4b48-91f3-0a8bc8f69559", | ||
84 | "image_url": "", | 84 | "image_url": "", | ||
85 | "is_organization": true, | 85 | "is_organization": true, | ||
86 | "name": "no-organization", | 86 | "name": "no-organization", | ||
87 | "state": "active", | 87 | "state": "active", | ||
88 | "title": "No Organization", | 88 | "title": "No Organization", | ||
89 | "type": "organization" | 89 | "type": "organization" | ||
90 | }, | 90 | }, | ||
91 | "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559", | 91 | "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559", | ||
92 | "private": false, | 92 | "private": false, | ||
93 | "relationships_as_object": [], | 93 | "relationships_as_object": [], | ||
94 | "relationships_as_subject": [], | 94 | "relationships_as_subject": [], | ||
t | 95 | "resources": [], | t | 95 | "resources": [ |
96 | { | ||||
97 | "cache_last_updated": null, | ||||
98 | "cache_url": null, | ||||
99 | "created": "2024-12-16T18:25:30", | ||||
100 | "data": [ | ||||
101 | "dcterms:title", | ||||
102 | "dcterms:accessRights", | ||||
103 | "dcterms:creator", | ||||
104 | "dcterms:description", | ||||
105 | "dcterms:issued", | ||||
106 | "dcterms:language", | ||||
107 | "dcterms:identifier", | ||||
108 | "dcat:theme", | ||||
109 | "dcterms:type", | ||||
110 | "dcat:keyword", | ||||
111 | "dcat:landingPage", | ||||
112 | "dcterms:hasVersion", | ||||
113 | "dcterms:format", | ||||
114 | "mls:task", | ||||
115 | "datacite:isDescribedBy" | ||||
116 | ], | ||||
117 | "description": "The json representation of the dataset with its | ||||
118 | distributions based on DCAT.", | ||||
119 | "format": "JSON", | ||||
120 | "hash": "", | ||||
121 | "id": "3c983003-3a20-4ec1-9a10-160303207076", | ||||
122 | "last_modified": "2024-12-16T17:43:57.104705", | ||||
123 | "metadata_modified": "2024-12-16T17:43:57.116139", | ||||
124 | "mimetype": "application/json", | ||||
125 | "mimetype_inner": null, | ||||
126 | "name": "Original Metadata", | ||||
127 | "package_id": "74265c60-b09f-47fe-9d34-23bcbb9ce452", | ||||
128 | "position": 0, | ||||
129 | "resource_type": null, | ||||
130 | "size": 906, | ||||
131 | "state": "active", | ||||
132 | "url": | ||||
133 | resource/3c983003-3a20-4ec1-9a10-160303207076/download/metadata.json", | ||||
134 | "url_type": "upload" | ||||
135 | } | ||||
136 | ], | ||||
96 | "services_used_list": "", | 137 | "services_used_list": "", | ||
97 | "state": "active", | 138 | "state": "active", | ||
98 | "tags": [ | 139 | "tags": [ | ||
99 | { | 140 | { | ||
100 | "display_name": "Anomaly Detection", | 141 | "display_name": "Anomaly Detection", | ||
101 | "id": "772b074e-4795-4f11-80b4-362b2f8a0dca", | 142 | "id": "772b074e-4795-4f11-80b4-362b2f8a0dca", | ||
102 | "name": "Anomaly Detection", | 143 | "name": "Anomaly Detection", | ||
103 | "state": "active", | 144 | "state": "active", | ||
104 | "vocabulary_id": null | 145 | "vocabulary_id": null | ||
105 | }, | 146 | }, | ||
106 | { | 147 | { | ||
107 | "display_name": "KPIs", | 148 | "display_name": "KPIs", | ||
108 | "id": "53c90f01-fdb7-47f0-9c73-53c4cebd905e", | 149 | "id": "53c90f01-fdb7-47f0-9c73-53c4cebd905e", | ||
109 | "name": "KPIs", | 150 | "name": "KPIs", | ||
110 | "state": "active", | 151 | "state": "active", | ||
111 | "vocabulary_id": null | 152 | "vocabulary_id": null | ||
112 | }, | 153 | }, | ||
113 | { | 154 | { | ||
114 | "display_name": "Seasonal Patterns", | 155 | "display_name": "Seasonal Patterns", | ||
115 | "id": "48262e43-be5c-4110-b2ec-0afb7e276c75", | 156 | "id": "48262e43-be5c-4110-b2ec-0afb7e276c75", | ||
116 | "name": "Seasonal Patterns", | 157 | "name": "Seasonal Patterns", | ||
117 | "state": "active", | 158 | "state": "active", | ||
118 | "vocabulary_id": null | 159 | "vocabulary_id": null | ||
119 | } | 160 | } | ||
120 | ], | 161 | ], | ||
121 | "title": "Unsupervised Anomaly Detection via Variational | 162 | "title": "Unsupervised Anomaly Detection via Variational | ||
122 | Auto-Encoder for Seasonal KPIs in Web Applications", | 163 | Auto-Encoder for Seasonal KPIs in Web Applications", | ||
123 | "type": "dataset", | 164 | "type": "dataset", | ||
124 | "version": "" | 165 | "version": "" | ||
125 | } | 166 | } |