(Containing rating and timestamp information)
(Note: We utilize the Pearson's coefficient to measure the similiarities in the KNN algorithm)
(Source : https://grouplens.org/datasets/movielens/)
| Entity | #Entity |
|---|---|
| User | 943 |
| Age | 8 |
| Occupation | 21 |
| Movie | 1,682 |
| Genre | 18 |
| Relation | #Relation |
|---|---|
| User - Movie | 100,000 |
| User - User (KNN) | 47,150 |
| User - Age | 943 |
| User - Occupation | 943 |
| Movie - Movie (KNN) | 82,798 |
| Movie - Genre | 2,861 |
(Containing rating information)
| Entity | #Entity |
|---|---|
| User | 13,367 |
| Movie | 12,677 |
| Group | 2,753 |
| Actor | 6,311 |
| Director | 2,449 |
| Type | 38 |
| Relation | #Relation |
|---|---|
| User - Movie | 1,068,278 |
| User - Group | 570,047 |
| User - User | 4,085 |
| Movie - Actor | 33,587 |
| Movie - Director | 11,276 |
| Movie - Type | 27,668 |
(Containing rating information)
| Entity | #Entity |
|---|---|
| User | 13,024 |
| Book | 22,347 |
| Group | 2,936 |
| Location | 38 |
| Author | 10,805 |
| Publisher | 1,815 |
| Year | 64 |
| Relation | #Relation |
|---|---|
| User - Book | 792,062 |
| User - Group | 1,189,271 |
| User - User | 169,150 |
| User - Location | 10,592 |
| Book - Author | 21,907 |
| Book - Publisher | 21,773 |
| Book - Year | 21,192 |
(Containing rating and timestamp information)
(Source : http://jmcauley.ucsd.edu/data/amazon/)
| Entity | #Entity |
|---|---|
| User | 6,170 |
| Item | 2,753 |
| View | 3,857 |
| Category | 22 |
| Brand | 334 |
| Relation | #Relation |
|---|---|
| User - Item | 195,791 |
| Item - View | 5,694 |
| Item - Category | 5,508 |
| Item - Brand | 2,753 |
(Note: We utilize the Pearson's coefficient to measure the similiarities in the KNN algorithm)
(Source : https://grouplens.org/datasets/hetrec-2011/)
| Entity | #Entity |
|---|---|
| User | 1,892 |
| Artist | 17,632 |
| Tag | 11,945 |
| Relation | #Relation |
|---|---|
| User - Artist | 92834 |
| User - User (Original) | 25,434 |
| User - User (KNN) | 18,802 |
| Artist - Artist (KNN) | 153,399 |
| Artist - Tag | 184,941 |
(Containing rating information)
| Entity | #Entity |
|---|---|
| User | 16,239 |
| Business | 14,284 |
| Compliment | 11 |
| Category | 47 |
| City | 511 |
| Relation | #Relation |
|---|---|
| User - Business | 198,397 |
| User - User | 158,590 |
| User - Compliment | 76,875 |
| Business - City | 14,267 |
| Business - Category | 40,009 |
(Containing rating information)
| Entity | #Entity |
|---|---|
| User | 1,286 |
| Business | 2,614 |
| Service | 2 |
| Star level | 9 |
| Reservation | 2 |
| Category | 3 |
| Relation | #Relation |
|---|---|
| User - Business | 30,838 |
| Bussiness - Service | 2,614 |
| Bussiness - Star level | 2,614 |
| Business - Revervation | 2,614 |
| Business - Category | 2,614 |
(Note: author_map_id.dat map the author id to the unique id)
| Entity | #Entity |
|---|---|
| Author | 14,475 |
| Paper | 14,376 |
| Author_label | 4 |
| Conference | 20 |
| Type | 8,920 |
| Relation | #Relation |
|---|---|
| Author - Label | 4,057 |
| Paper - Author | 41,794 |
| Paper - Conference | 14,376 |
| Paper - Type | 114,624 |
(Note: author_map_id.dat map the author id to the unique id)
| Entity | #Entity |
|---|---|
| Author | 164,472 |
| Paper | 127,623 |
| Papel_label | 10 |
| Conference | 101 |
| Reference | 147,251 |
| Relation | #Relation |
|---|---|
| Paper - Label | 127,623 |
| Paper - Author | 355,072 |
| Paper - Conference | 127,632 |
| Paper - Reference | 392,519 |
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent