DOI: 10.5281/zenodo.13328257
title: Examining Patented Artefact Knowledge Graphs to understand Linguistic and Structural Basis

description: Introduction

This resource is uploaded in support of our research that involves examining knowledge graphs of patented artefacts to understand the linguistic and structural basis of engineering design knowledge. The research is detailed in the following paper.

https://arxiv.org/abs/2312.06355

The resource is segregated into multiple Pandas dataframes in pickled format – “.pkl”. To access any dataframe, please use the following Python code.

import pandas as pd

data = pd.read_pickle("PATH TO FILE.pkl")
print(data.head())

The individual datasets are described as follows.
description: Patent Data

The original patent data is given in "engineering-design-knowledge/1-patent-data/"

For our analysis, we sampled 33,881 patents from USPTO using Patents View such that these are stratified according to the CPC subclasses. 

Patent List

In the dataframe "1-patent-list.pkl", we provide the introductory information about these patents as follows.




FIELD
EXAMPLE


patent_id
7745779


patent_date
29/6/2010


patent_title
Color pixel arrays having common color filters for multiple adjacent pixels for use in CMOS imagers


patent_abstract
Image sensors and methods of operating image sensors. An image sensor includes an array of pixels and an array of color filters …


patent_classifications
['H04N', 'G01J']




Patent Sentences

From each patent in the dataset as described above, we acquire the full-text and process the sentences in these. In the dataframe "2-patent-sentences.pkl", we provide the list of 7,566,829 formatted sentences along with patent ID and lengths in terms of token count.




FIELD
EXAMPLE


patent_id
10716120


sentence_id
10716120_725


sentence
In certain examples, aspects of the operations of block 1915 may be performed by an uplink component as described with reference to FIGS 14 through 17.


length
28




Patent Knowledge Graphs

From the sentences as described above, we extracted 24,537,587 facts of the form - head entity :: relationship :: tail entity using a method described in our prior work - https://arxiv.org/abs/2307.06985

Combining these facts within a patent would form a patent knowledge graph that we examined in the current work to understand basis of design knowledge. The dataframe "3-patent-knowledge-graphs.pkl" provides individual facts as follows. The sentence ID in each row is same as the one mentioned in the previous dataframe - "2-patent-sentences.pkl".




FIELD
EXAMPLE


patent_id
10075499


sentence_id
10075499_98


head
the host facility


relation
with


tail
the highest average and aggregate weighting value




We combine facts as described above, within a patent, to get a knowledge graph that is used for examination in our current work. The results of our analysis are compiled into dataframes as explained below.
description: Linguistic Basis

We analysed the frequencies of entities and relationships in the knowledge graphs populated for each patent in the sample. In the dataframes provided under "engineering-design-knowledge/2-linguistic-basis/", we provide information for 5,015,681 entities, 845,303 relationships, and 165 hierarchical relationships regarding their frequencies and linguistic syntaxes. In our work, we fit the proportions of the syntaxes to a Zipf distribution to visualise these at different percentiles.

Entity Syntaxes




FIELD
EXAMPLE


entity
the upper connecting member


frequency
27


syntax
the JJ VBG NN




Relation Syntaxes




FIELD
EXAMPLE


entity
are suitable for recovering


frequency
2


syntax
are JJ for VBG




Hierarchical Relation Syntaxes




FIELD
EXAMPLE


hierarchical_relation
comprises determining


count
1237


syntax
compris* VBG




 
description: Structural Basis

We did motif analysis on the network structures of the patent knowledge graphs to identfy statistically recurrent 3-node and 4-node patterns that are building blocks for each patent knowledge graph. In the dataframe - "1-patent-motifs.pkl" under "engineering-design-knowledge/3-structural-basis/", we list the network size and the motifs for each patent in the sample.




FIELD
EXAMPLE


patent_id
9139018


node_count
85


edge_count
146


motifs
[5, 61, 80]




The pattern # mentioned in the motifs field as above could be references using the images included in the folder "pattern-figures".