https://eureka.patsnap.com/resources/blog/rd-blog/open-source-software-license-text-classification-using-machine-learning-patent-landscape/ · Patsnap · data cut-off 2026-10-22 · downloaded from the live page
Patent Landscape · Patent Landscape Snapshot

Open Source Software License Text Classification Using Machine Learning Patents

A 17-family dataset on classifying open-source license text with machine learning, led by a filer with 3 families.

30
Published Records
17
Simple Patent Families
43%
In Force at Cut-off
US
Leading Jurisdiction

30 published records collapse into 17 simple (DOCDB) families; the difference is the same invention filed in more than one country. In force = 13 of 30 records still granted and maintained at the data cut-off; the rest are pending, withdrawn, refused or lapsed.

  • 17 simple patent families sit behind 30 published records on classifying open-source license text with machine learning, with no date limit set on the search.
  • AMAZON TECH INC is named on 3 of the 17 simple patent families (17.6%), the largest single-row share in the listed filers.
  • 10 of the 11 listed filers hold 2 or fewer simple patent families each, the long tail in this dataset.
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Published byPatsnap Research··6 min readSourced from Patsnap Eureka
Overview

What this dataset covers

This landscape tracks records matching a search for open-source license text handled by machine learning, text classification or classifier methods. The underlying search string requires the terms to co-occur in the title, abstract or claims, which keeps the pool narrow: 17 simple patent families and 30 published records in total, with no date limit applied.

17 families is a small pool. The figures below describe what this particular search returned, not the shape of a field or industry, treat this page as a starting point for a deeper search rather than a finished map.

Records vs. families in scope
  1. AMAZON TECH INC3
  2. KYNDRYL INC1
  3. WHITE SOURCE1
  4. FOSSITY AUDITING SL1
  5. OPEN WEAVER INC1
  6. ORULA INC1
  7. BINARLY INC1
  8. BLACK DUCK SOFTWARE INC1
  9. TNTRA INC1
  10. MICROSOFT TECHNOLOGY LICENSING LLC1

Ordered by volume only, not by importance or claim strength. Counted in simple (DOCDB) patent families, so one invention filed in several countries counts once. Names come from Patsnap's standardised assignee field as recorded on each document; subsidiaries and group companies are not merged. The icon before each name is read from the name itself (words such as University, Institute or Ltd); the data carries no organisation-type field, so treat it as a reading aid rather than a classification. Filings held by named individuals rather than organisations are removed where they can be identified (4 here); that identification is not exhaustive, so an individually held filing can still appear below. Either way those filings stay inside the totals above. This table shows the top 11 of the 11 filers returned for this search; the data endpoint returns at most 100 entities, so even that 11 is not the complete set of filers. A single family can name more than one filer, so these counts overlap and do not add up to the total.

Source: Patsnap Eureka. Assignee ranking and totals. Derived from one Patsnap search for Open Source Software License Text Classification Using Machine Learning Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-22. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
The Numbers

Filing trend and technology composition

Two views of the same 17-family, 30-record dataset: when records were first filed, and which IPC subclasses they carry.

Filing trend (published records, by earliest filing year)

Records run from a single filing in 2012 up to 2 in 2026, with a peak of 9 in 2021. The years from 2022 onward are still filling in as later filings publish, so the recent downturn on the chart reflects publication lag rather than fewer filings.

Filing trend (published records, by earliest filing year)035810120122014201620182020920222024220262022 onwards are shaded as still filling in: a filing is only visible once it publishes, up to 30 months after filing.

Counted in published records by earliest filing year, not de-duplicated into families. A filing is counted in the year it was filed, but it only becomes visible after it publishes: roughly 18 months for most routes, and up to 30 months where a PCT application enters national phase. 2022 onwards are therefore still filling in and are shaded; no growth figure on this page uses them. Because this series counts documents rather than inventions, a rise can mean more inventions or the same inventions filed in more countries; this dataset cannot separate the two.

Technology composition (share of 17 simple patent families)

G06F (electric digital data processing) appears on 13 of the 17 families (76.5%), G06N (computing based on AI models) on 10 (58.8%), and G06Q (business, commerce & admin data processing) on 3 (17.6%). A family can carry more than one of these classes, so the shares add up to more than 100%.

Technology composition (share of 17 simple patent families)G06F · Electric digital data processi…1376.5%G06N · Computing based on AI models1058.8%G06Q · Business, commerce & admin dat…317.6%G16H · Healthcare informatics211.8%A61B · Diagnosis & surgery15.9%A61G · Patient transport & care15.9%A61L · Sterilising & disinfecting15.9%C08J · Polymer processing & solutions15.9%Other317.6%

Shares are the percentage of the 17 patent families in scope. One patent family can carry several IPC classes, so the shares add up to more than 100%.

Source: Patsnap Eureka. Filing trend and technology composition. Derived from one Patsnap search for Open Source Software License Text Classification Using Machine Learning Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-22. Counts cover published records only and move as new filings publish.

Go deeper on Open Source Software License Text Classification Using Machine Learning Patent Landscape with Eureka

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Example Record

A record from the result set

From the result set
US20250322336A12025-10-16

Machine Learning-Based Approach to Characterize Software Supply Chain Risk

BINARLY INC

A software package is received and unpacked into a plurality of components. Features are extracted from each component indicative of whether it presents a software supply chain risk, and one or more machine learning models consume those features to determine a risk level that can be provided to a consuming application or process. Component identities can also be identified using machine learning or other similarity analyses, in some cases using embeddings to characterize risk or provide component identities.US20250322336A1, BINARLY INC, filed 2025-10-16. Shown as the database's default first result, not as the most cited, newest or broadest record in scope.

US20250322336A1, patent drawing 1US20250322336A1, patent drawing 2
View full record

Selected as the first record the search returns under the database default order, then shown in full. It is not ranked by citations, claim breadth or commercial importance, and it is not a judgement about which filing in this space matters most.

Source: Patsnap Eureka. The first record the search returned, shown in full. Derived from one Patsnap search for Open Source Software License Text Classification Using Machine Learning Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-22. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
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Key Figures

What the numbers show

Three figures taken directly from the dataset, each counted in the unit stated.

Filer concentration
17.6%
largest single-row share

One row holds 3 of 17 families

AMAZON TECH INC is named on 3 of the 17 simple patent families in scope (17.6%). This is a single-row figure; filer rows are not rolled up to corporate group and cannot be added together, since one family can name several filers.

Source: filer list, 11 entities (organisations only)
Long tail
10 of 11
filers with 2 or fewer families

Most listed filers hold 1–2 families

10 of the 11 listed filers hold 2 or fewer simple patent families each. Filings held by named individuals are excluded from this list but remain inside the 17-family and 30-record totals.

Source: filer list, counted in simple patent families
Technology split
76.5% / 58.8%
share of 17 families

G06F and G06N carry most of the IPC mix

G06F (electric digital data processing) appears on 13 of 17 families and G06N (computing based on AI models) on 10 of 17. Since a family can carry both classes, these shares add up to more than 100% and are not mutually exclusive.

Source: IPC subclass breakdown, 17 families
Legal status
13 of 30
records granted and in force

43% of records are in force at retrieval

13 of the 30 published records (43%) were granted and still in force at the 2026-10-22 retrieval date. This is a legal-status snapshot at one point in time, not a measure of which filings are strongest.

Source: legal status at retrieval
Eureka AI Agent
Looking for what nobody has claimed yet?

Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to open source software license text classification using machine learning patent landscape, with the prior art for and against each one.

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Source: Patsnap Eureka. Derived observations on the same dataset. Derived from one Patsnap search for Open Source Software License Text Classification Using Machine Learning Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-22. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
Next Steps

Going deeper than this snapshot

This page surfaces counts and classes; the follow-up work is reading claims and tracking specific filers.

Read the granted claims directly

A family count or an abstract cannot establish what a granted claim covers. Pull the claim sets for any record that matters to a specific product decision.

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Track filer activity over time

The filer list here is a snapshot of volume, not of intent or strategy. Watching new filings from the same names over time gives a fuller picture than one count.

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Widen or narrow the search string

A 17-family pool this small is sensitive to the exact terms used. Adjusting the search string can surface adjacent records this page's terms missed.

Refine this search in Eureka
Source: Patsnap Eureka. Suggested next steps. No new data: every figure named here is one of those above. Derived from one Patsnap search for Open Source Software License Text Classification Using Machine Learning Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-22. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
FAQ

Common questions about this dataset

Answers are grounded in the same dataset. Derived from one Patsnap search for Open Source Software License Text Classification Using Machine Learning Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-22. Counts cover published records only and move as new filings publish.Run this in Eureka MCP

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Go past this page: query the whole open source software license text classification using machine learning patent landscape corpus yourself, in your own scope.
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How this page was built, and what the numbers do and do not mean

Search. Every figure on this page comes from one Patsnap search, run once and not edited afterwards. This is the exact search string:

TAC:(("open source" OR "open-source") AND license AND ("machine learning" OR "text classification" OR classifier))

Reading the field codes: TAC searches the title, abstract and claims of each record, not the full description. The search string sets no date limit, so the scope is every matching record in the database regardless of when it was filed. It is not restricted to recent years. How this string was built matters for how far the counts can be pushed. It was generated in batch from a topic list rather than hand-crafted for this page, and the result set is not manually screened. A keyword search over title, abstract and claims both over-captures (unrelated filings that happen to use the same words) and under-captures (the same invention written in different words). This page cannot measure either effect, so read every figure here as what this particular string returned, not as what exists in the field. One subclass (G06F) carries 76.5% of the patent families, so this search returned a classification-tight set.

What is being counted. Two different units appear on this page and they are not interchangeable. The filer list and the technology split are counted in simple (DOCDB) patent families: one invention counts once however many countries it was filed in. The total, the jurisdiction split and the filing-year chart are counted in published records: the same invention counts once per publication. For this search that is 30 records and 17 families. Record counts reward filing in many jurisdictions; family counts do not. Shares are only ever taken against a denominator in the same unit, and each one names it.

Who the filers are. Names come from Patsnap's standardised assignee field, as recorded on the documents themselves. They are not rolled up to corporate group: a parent and its subsidiaries appear as separate entries, and a portfolio acquired from another company stays under the name on the document unless the assignment is reflected there. This list is meant to carry organisations, not people. Filings held by a named individual are identified by matching the assignee against the inventors on the same search, and, for names written in Chinese, Japanese or Korean characters, by the name carrying no organisational suffix; those are removed from the list (4 of them here). Neither test is exhaustive: the inventor list it matches against is itself capped, and a personal name written in Latin script with no organisational wording in it cannot be told apart from a short company name by rule. So an individually held filing can still appear in the list. Those filings stay inside every total and share on this page either way, so the listed entries can add up to less than the total. A record shown in full further down still names its assignee exactly as the patent office records it, including where that is a person: that name is how the record is identified and checked. What is left out of the ranking is people as ranked entries, not people as cited sources. The table shows the top 11 of the 11 filers returned, ordered by count alone; the data endpoint returns at most 100 entities, so even that 11 is not every filer. One patent family can name several filers and each is counted separately, so these rows are not slices of a divided whole: adding them together over-counts, and this page deliberately publishes no combined "top five" share for that reason. See every filer, individuals included

Dates. The year chart counts by earliest filing year, not publication year. A filing only becomes visible once it publishes: roughly 18 months for most routes, and up to 30 months where a PCT application enters national phase. Measured across these pages, the year four back from today still holds only about 89% of its eventual count. 2022 onwards are therefore shaded on the chart as still filling in. The data behind this page was retrieved on 2026-10-22.

Legal status. "In force" counts documents whose legal status at retrieval was granted and maintained (13 of 30). Everything else is pending, withdrawn, refused, lapsed or not determinable, and those states are not broken out here because the underlying codes do not separate them cleanly. Legal status changes continuously and is reported per document, not per family. Get the status breakdown in Eureka

Classification. The technology split uses IPC subclasses (four characters, for example H01M). A single record usually carries several, so the shares add up to more than 100% and a record can appear in more than one bar. Subclass is a coarse grouping; it describes the field a record was classified into, not what the claims cover. Break the classes down to subgroup level

Who wrote the words. The tables, charts, counts, shares and patent numbers on this page are produced directly from the search result by a program; none of them are written or estimated by a language model. The surrounding prose, headings, FAQ answers and the answers in the question panel are drafted by a language model that is given those same figures and is not permitted to introduce others. Prose can still mis-describe a correct figure, so where the two disagree, the tables and charts are the record.

Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.

Patent data carries limitations that apply to every figure above. Recent filings are under-counted, because an application is not public until roughly 18 months after filing and database loading adds further delay. The search string defines and constrains everything shown: records that use different terminology, or that sit outside the fields searched, are absent and cannot be counted. Applicant names, classification codes, legal-status codes and citation records are taken as recorded and may contain errors, duplicates, omissions or stale entries. Ordering by volume is not a measure of quality, scope, enforceability or commercial value, and a larger portfolio is not a stronger one. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.

Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, validity or infringement search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. No attorney-client relationship is created by it. Any patent, commercial, or strategic decision should be verified independently against the primary records and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.

The question panel. The answers behind the suggested questions on this page were written when the page was generated, not in response to your click. The progress steps that play before an answer appears are an animation of how that analysis was done; nothing is being searched or computed at that moment. Typing your own question instead opens Patsnap Eureka, which does run it live.

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