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https://github.com/alixaxel/pagerank
Weighted PageRank implementation in Go
https://github.com/alixaxel/pagerank
algorithms go golang pagerank
Last synced: about 2 months ago
JSON representation
Weighted PageRank implementation in Go
- Host: GitHub
- URL: https://github.com/alixaxel/pagerank
- Owner: alixaxel
- License: mit
- Created: 2015-08-06T01:33:34.000Z (almost 9 years ago)
- Default Branch: master
- Last Pushed: 2021-06-19T22:18:08.000Z (about 3 years ago)
- Last Synced: 2024-01-31T05:50:23.116Z (5 months ago)
- Topics: algorithms, go, golang, pagerank
- Language: Go
- Size: 8.79 KB
- Stars: 78
- Watchers: 9
- Forks: 21
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
Lists
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go-extra - pagerank - 08-06T01:33:34Z|2021-06-19T22:18:08Z| (Science and Data Analysis / HTTP Clients)
- awesome-go-zh - pagerank
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go - pagerank - | - | - | (Science and Data Analysis / HTTP Clients)
- fucking-awesome-go - :octocat: pagerank - Weighted PageRank algorithm implemented in Go :star: 13 :fork_and_knife: 4 (Science and Data Analysis / Advanced Console UIs)
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go-projects - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go (Science and Data Analysis / Advanced Console UIs)
- awesome-go-with-framework - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go-cn - pagerank
- awesome-go-stars - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- zero-alloc-awesome-go - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go (Science and Data Analysis / Advanced Console UIs)
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-Char - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go. - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / Advanced Console UIs)
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go. (<span id="科学和数据分析-science-and-data-analysis">科学和数据分析 Science and Data Analysis</span> / <span id="高级控制台用户界面-advanced-console-uis">高级控制台用户界面 Advanced Console UIs</span>)
- awesome-go-cn - pagerank - Go 语言实现的加权网页排名（ PageRank）算法 (科学及数据分析 / 高级控制台界面)
- awesome-go-with-stars - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- repo-1316-awesome-go-cn - pagerank
- repo-1211-awesome-go-cn - pagerank
- awesome-reader - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- Go-awesome - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / Advanced Console UIs)
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go (Science and Data Analysis / Advanced Console UIs)
- awesome-go-cn - pagerank
- awesome-go-handwritten - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go - pagerank - Go 語言實現的加權網頁排名（ PageRank）算法 (科學及數據分析 / 高級控制台界面)
- awesome-go2 - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / Advanced Console UIs)
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go. - :arrow_down:3 - :star:17 (Science and Data Analysis / HTTP Clients)
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go (Science and Data Analysis / Advanced Console UIs)
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go-cn - pagerank
- awesome-go-zh - pagerank
- awesome-go-cn - pagerank
- awesome-go-cn - pagerank
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go - pagerank - Weighted PageRank algorithm implemented in Go. (Science and Data Analysis / HTTP Clients)
- awesome-go - pagerank - Weighted PageRank implementation in Go - ★ 41 (Science and Data Analysis)
- go-awesome-cn-star - pagerank
README
# pagerank [](https://godoc.org/github.com/alixaxel/pagerank) [](http://gocover.io/github.com/alixaxel/pagerank) [](https://goreportcard.com/report/github.com/alixaxel/pagerank)
Weighted PageRank implementation in Go
## Usage
```go
package main
import (
"fmt"
"github.com/alixaxel/pagerank"
)
func main() {
graph := pagerank.NewGraph()
graph.Link(1, 2, 1.0)
graph.Link(1, 3, 2.0)
graph.Link(2, 3, 3.0)
graph.Link(2, 4, 4.0)
graph.Link(3, 1, 5.0)
graph.Rank(0.85, 0.000001, func(node uint32, rank float64) {
fmt.Println("Node", node, "has a rank of", rank)
})
}
```
## Output
```
Node 1 has a rank of 0.34983779905464363
Node 2 has a rank of 0.1688733284604475
Node 3 has a rank of 0.3295121849483849
Node 4 has a rank of 0.15177668753652385
```
## Install
go get github.com/alixaxel/pagerank
## License
MIT