| Nome |
# |
|
Brotli: A General-Purpose Data Compressor, file e0d6c92b-5abc-fcf8-e053-d805fe0aa794
|
333
|
|
On the bit-complexity of Lempel-Ziv compression, file e0d6c92c-3070-fcf8-e053-d805fe0aa794
|
297
|
|
null, file e0d6c926-7b96-fcf8-e053-d805fe0aa794
|
262
|
|
Distribution-aware compressed full-text indexes, file e0d6c92b-ef95-fcf8-e053-d805fe0aa794
|
180
|
|
Compressed Indexes for String Searching in Labeled Graphs, file e0d6c926-7b94-fcf8-e053-d805fe0aa794
|
156
|
|
A public data set of spatio-temporal match events in soccer competitions, file e0d6c92d-e6c2-fcf8-e053-d805fe0aa794
|
146
|
|
Document aboutness via sophisticated syntactic and semantic features, file e0d6c92a-b7c4-fcf8-e053-d805fe0aa794
|
135
|
|
Bicriteria data compression, file e0d6c92c-339c-fcf8-e053-d805fe0aa794
|
120
|
|
Swat: A system for detecting salient Wikipedia entities in texts, file e0d6c92d-9246-fcf8-e053-d805fe0aa794
|
111
|
|
PlayeRank: Data-driven performance evaluation and player ranking in soccer via a machine learning approach, file e0d6c930-6de5-fcf8-e053-d805fe0aa794
|
91
|
|
Wiser: A semantic approach for expert finding in academia based on entity linking, file e0d6c930-df8e-fcf8-e053-d805fe0aa794
|
72
|
|
Bicriteria Data Compression, file e0d6c92e-1073-fcf8-e053-d805fe0aa794
|
71
|
|
ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health, file ff31030f-0b35-4ba7-92f2-b51fadec81dc
|
58
|
|
GERBIL: General Entity Annotator Benchmarking Framework, file e0d6c930-bd13-fcf8-e053-d805fe0aa794
|
51
|
|
On Analyzing Hashtags in Twitter, file e0d6c92c-8565-fcf8-e053-d805fe0aa794
|
33
|
|
A "Learned" Approach to Quicken and Compress Rank/Select Dictionaries, file 45c2a194-4562-4144-8c19-39b0cf2ffc08
|
16
|
|
Two-stage framework for computing entity relatedness in Wikipedia, file e0d6c92c-5871-fcf8-e053-d805fe0aa794
|
15
|
|
Improving Matrix-vector Multiplication via Lossless Grammar-Compressed Matrices, file 1665f759-f570-41e2-8a57-552157559117
|
13
|
|
Why are learned indexes so effective?, file e0d6c92f-bd00-fcf8-e053-d805fe0aa794
|
12
|
|
Motif-Raptor: a cell type-specific and transcription factor centric approach for post-GWAS prioritization of causal regulators, file e0d6c931-4feb-fcf8-e053-d805fe0aa794
|
11
|
|
NETME: on-the-fly knowledge network construction from biomedical literature, file e0d6c931-e478-fcf8-e053-d805fe0aa794
|
11
|
|
Locality Filtering for Efficient Ride Sharing Platforms, file 64f177d8-0e9b-4d79-828c-6c12b1e76816
|
8
|
|
null, file e0d6c927-a428-fcf8-e053-d805fe0aa794
|
8
|
|
Contextualizing Trending Entities in News Stories, file e0d6c931-7213-fcf8-e053-d805fe0aa794
|
7
|
|
Pearls of Algorithm Engineering, file 9e02e872-4569-44b1-87be-6779eb3589d9
|
5
|
|
A piggyback system for joint entity mention detection and linking in web queries, file e0d6c928-6bb6-fcf8-e053-d805fe0aa794
|
5
|
|
Web Search, file e0d6c92c-3393-fcf8-e053-d805fe0aa794
|
4
|
|
On the performance of learned data structures, file e0d6c931-85b3-fcf8-e053-d805fe0aa794
|
4
|
|
Grafite: Taming Adversarial Queries with Optimal Range Filters, file 08bc554e-0b3a-47e2-a119-8f5191c848af
|
3
|
|
On Nonlinear Learned String Indexing, file a23d9fe8-23ce-405a-b361-fa183501ebf1
|
3
|
|
Compressing and Querying Integer Dictionaries Under Linearities and Repetitions, file b2cfaead-6ebb-49fb-befc-d8b1b74301ae
|
3
|
|
On the weak prefix-search problem, file e0d6c92c-339e-fcf8-e053-d805fe0aa794
|
3
|
|
Give more data, awareness and control to individual citizens, and they will help COVID-19 containment, file e0d6c931-99fe-fcf8-e053-d805fe0aa794
|
3
|
|
BioTAGME: A Comprehensive Platform for Biological Knowledge Network Analysis, file 35acf9d0-f5f6-4a1e-b7b4-727c7329fa4b
|
2
|
|
Learned Monotone Minimal Perfect Hashing, file 512745a8-4871-4dba-a6fd-487c90883d53
|
2
|
|
Boosting Textual Compression, file e0d6c92c-2b85-fcf8-e053-d805fe0aa794
|
2
|
|
Indexed Two-Dimensional String Matching, file e0d6c92c-2b87-fcf8-e053-d805fe0aa794
|
2
|
|
Compressed Cache-Oblivious String B-tree, file e0d6c92c-3072-fcf8-e053-d805fe0aa794
|
2
|
|
Bicriteria Data Compression: Efficient and Usable, file e0d6c92c-339a-fcf8-e053-d805fe0aa794
|
2
|
|
On Computing Entity Relatedness in Wikipedia, with Applications, file e0d6c92d-e6cc-fcf8-e053-d805fe0aa794
|
2
|
|
Learned Data Structures, file e0d6c92e-a6e2-fcf8-e053-d805fe0aa794
|
2
|
|
Early outcome detection for COVID-19 patients, file e0d6c931-a114-fcf8-e053-d805fe0aa794
|
2
|
|
Data structures and operations for searching, computing, and indexing in DNA-based storage, file f41cf04f-b568-4dd9-a18d-55ca97487fc0
|
2
|
|
Contextualizing Trending Entities in News Stories, file f97df690-0b0c-4095-9db2-6cb3809abd92
|
2
|
|
CoCo-trie: Data-aware compression and indexing of strings, file 74467fd3-c79a-4895-91ce-b45494577f6d
|
1
|
|
Suffix Tree Construction in Hierarchical Memory, file e0d6c92b-ea21-fcf8-e053-d805fe0aa794
|
1
|
|
From TagME to WAT: a new entity annotator, file e0d6c92b-ebe1-fcf8-e053-d805fe0aa794
|
1
|
|
Burrows-Wheeler Transform, file e0d6c92c-2b8a-fcf8-e053-d805fe0aa794
|
1
|
|
The SMAPH system for query entity recognition and disambiguation, file e0d6c92c-2b90-fcf8-e053-d805fe0aa794
|
1
|
|
Compressing and Indexing Structured Text, file e0d6c92c-31bc-fcf8-e053-d805fe0aa794
|
1
|
|
null, file e0d6c92c-8726-fcf8-e053-d805fe0aa794
|
1
|
|
A framework for benchmarking entity-annotation systems, file e0d6c92c-bf02-fcf8-e053-d805fe0aa794
|
1
|
|
The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds, file e0d6c92e-d36e-fcf8-e053-d805fe0aa794
|
1
|
|
SMAPH: A Piggyback Approach for Entity-Linking in Web Queries, file e0d6c930-a5e5-fcf8-e053-d805fe0aa794
|
1
|
|
Repetition- and Linearity-Aware Rank/Select Dictionaries, file e0d6c931-ac1d-fcf8-e053-d805fe0aa794
|
1
|
|
Linear time distributed swap edge algorithms, file e0d6c932-3fe1-fcf8-e053-d805fe0aa794
|
1
|
|
Machine learning to identify a composite indicator to predict cardiac death in ischemic heart disease, file e164c208-7c17-4bf1-96f8-77f31c8aa582
|
1
|
|
Bicriteria Data Compression: Efficient and Usable, file f2bb75dd-fe7b-4910-b921-7bf22a071f59
|
1
|
| Totale |
2.286 |