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Open Source Science

semanticpatents

https://github.com/justeraimbault/semanticpatents

Science Score: 41.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    1 of 1 committers (100.0%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (7.4%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: JusteRaimbault
  • Language: Jupyter Notebook
  • Default Branch: master
  • Size: 802 KB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Created almost 8 years ago · Last pushed almost 7 years ago
Metadata Files
Readme Citation

README.md

Setup

  • having a running local mongod instance
  • mongo host, port, user and password to be configured in conf/parameters.csv
  • raw data import from gz file : use mongorestore -d redbook -c raw --gzip $FILE
  • specific python packages required : pymongo, python-igraph, nltk (with resources punkt, averaged_perceptron_tagger,porter_test)

Running

The utility fullpipe.sh can launch most of the processing pipe.

Options :

(to be changed in conf/parameters.csv) - $WINDOW : window size in years - $START : beginning of first window - $END : beginning of last window - $NRUNS : number of parallel runs

Tasks :

The tasks to be done in order : keywords extraction, relevance estimation, network construction, semantic probas construction, are launched with the following options :

\!// keywords and kw-consolidation tested with python3 ; rest with python2 (igraph compatibility issues)

  • keywords : extracts keywords
  • kw-consolidation : consolidate keywords database (techno disp measure)
  • raw-network : estimates relevance, constructs raw network and perform sensitivity analysis
  • classification : classify and compute patent probability, keyword measures and patent measures

Analysis

  • preprocess the data in semanalfun.R

Data Collection

Raw Data Collection

Data Preprocessing

  • from csv technological classes to R-formatted sparse Matrix : use Techno/prepareData.R
  • from csv citation file to citation network in R-formatted graph and adjacency sparse matrix : use Citation/constructNW.R

Owner

  • Name: Juste Raimbault
  • Login: JusteRaimbault
  • Kind: user

Citation (Citation/constructNW.R) 

# construct citation network

setwd(paste0(Sys.getenv('CS_HOME'),'/PatentsMining/Data/processed/citation'))

library(igraph)
library(Matrix)

edf1 = read.csv(file=paste0(Sys.getenv('CS_HOME'),'/PatentsMining/Data/raw/citation/citation75_99/citation75_99.csv'),stringsAsFactors = FALSE)
edf2 = read.csv(file=paste0(Sys.getenv('CS_HOME'),'/PatentsMining/Data/raw/citation/citation00_10.csv'),stringsAsFactors = FALSE)

from = c(as.character(edf1[,1]),as.character(edf2[,1]))
to = c(as.character(edf1[,6]),as.character(edf2[,6]))

# keep uspto only
fromok=sapply(from,nchar)<=8
took=sapply(to,nchar)<=8
from = from[fromok&took]
to = to[fromok&took]

# apply : 7digits ids
from[sapply(from,nchar)==8] <- substr(from[sapply(from,nchar)==8],2,8)
to[sapply(to,nchar)==8] <- substr(to[sapply(to,nchar)==8],2,8)

#edf = rbind(edf1[,c(1,6)],edf2[,c(1,6)])
#names(edf)<-c("from","to")

edf = data.frame(from=from,to=to)

gcitation = graph_from_data_frame(edf)
citadjacency = get.adjacency(gcitation,sparse=TRUE)

save(gcitation,file='network/citationNetwork.RData')
save(citadjacency,file='network/adjacency.RData')

# check / validation

# size
# sum(citadjacency) = 53527305
# cat Data/raw/citation/citation00_10.csv | wc -l + cat Data/raw/citation/citation75_99/citation75_99.csv | wc -l
# = 16301993+37225314 = 53527307 : OK (+2 header)

# plot size INSIDE block in time.

#idlengths = sapply(rownames(citadjacency),nchar)
#idlengths[idlengths==8]

GitHub Events

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Last Year

Committers

Last synced: almost 2 years ago

All Time
  • Total Commits: 3
  • Total Committers: 1
  • Avg Commits per committer: 3.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Juste Raimbault j****t@p****u 3
Committer Domains (Top 20 + Academic)
polytechnique.edu: 1

Issues and Pull Requests

Last synced: over 1 year ago

All Time
  • Total issues: 0
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 0
  • Total pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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