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Run your analysis now →https://eureka.patsnap.com/resources/blog/rd-blog/learning-vector-quantization-prototype-based-classification-patent-landscape/ · Patsnap · data cut-off 2026-10-22 · downloaded from the live page
Patent Landscape · Artificial Intelligence & Machine LearningLearning Vector Quantization Prototype Classification Patents
A 6-family, 19-record dataset on learning vector quantization prototype classification, with no single top filer and filings spread across ten IPC subclasses.
19
Published Records
6
Simple Patent Families
37%
In Force at Cut-off
US
Leading Jurisdiction
19 published records collapse into 6 simple (DOCDB) families; the difference is the same invention filed in more than one country. In force = 7 of 19 records still granted and maintained at the data cut-off; the rest are pending, withdrawn, refused or lapsed.
- This search returns 19 published records condensed into 6 simple patent families. A pool this size supports a starting point for research, not a map of the field.
- Six filers each hold 1 or 2 simple patent families, with no single filer ahead of the rest. The largest row, INTELLIGENT INFORMATION SECURITY TECHNOLOGY INC, is named on 1 of the 6 families (16.7%).
- G06N (computing based on AI models) appears on 4 of the 6 families (66.7%). The next largest classes, G06F and G06K, each appear on 2 of the 6 families (33.3%).
Published byPatsnap Research··6 min readSourced from Patsnap Eureka
Overview
What this dataset covers
This page is built from a search for learning vector quantization (LVQ) and prototype-based methods combined with classification or classifier terms, run across patent titles, abstracts and claims. It returns 19 published records, which condense to 6 simple patent families once duplicate filings of the same invention across countries are merged. The search string carries no date limit, so the records span whatever years the matching documents happen to fall in; it also does not restrict the technology applied, so the result set reaches into fields outside core machine learning wherever the term combination appears.
With only 6 families in scope, this page is a starting point for a search rather than a map of the field. Small counts here reflect what this exact string returned, not the presence or absence of activity on learning vector quantization more broadly, a different phrasing could easily surface a different set.
Records vs. families in scope
Counted over all 19 published records, including filings from before 2009; the filing-trend chart below covers only the 16 records from 2009 onward, so the two charts are not the same set of documents. 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; 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 6 of the 6 filers returned for this search; the data endpoint returns at most 100 entities, so even that 6 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 Learning Vector Quantization Prototype Based Classification 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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Data
Filing activity and technology split
Figures below are drawn directly from the search result: a filing-trend chart counted in published records, and an IPC composition chart counted in simple patent families.
Filing trend by earliest filing year (16 of 19 published records)
Records are counted by earliest filing year, not de-duplicated into families, so one invention filed in several countries adds several marks. The chart shows a peak so far of 8 records in 2010; years from 2022 onward are still filling in as publications lag behind filing, so no decline should be read into the most recent years.
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. This chart covers 2009-2026 (16 records); the 19 total quoted above includes earlier filings outside the window.
IPC subclass composition
Each of the 6 simple patent families can carry more than one IPC subclass, so the shares below add up to more than 100%. G06N (computing based on AI models) appears on 4 of the 6 families (66.7%), followed by G06F (electric digital data processing) and G06K (data recognition & presentation) at 2 families each (33.3%).
Shares are the percentage of the 6 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 Learning Vector Quantization Prototype Based Classification 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 Learning Vector Quantization Prototype Based Classification Patent Landscape with Eureka
This page is one run against one query. Ask Eureka your own question about learning vector quantization prototype based classification patent landscape and every answer comes back with the patent numbers behind it.
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A record from the result set
From the result set
Context recognition in mobile devices
TEKNOLOGIAN TUTKIMUSKESKUS VTT
The abstract describes a mobile device with sensing entities that obtain context data, a feature-determination logic that derives representative feature values from that data, and a context-recognition logic built around an adaptive linear classifier. The classifier maps feature values to a context class and adapts its own classification logic using feedback from the device user.This is the first record returned under the database's default ordering, not the most cited, newest or broadest filing in the set. It is shown to illustrate one way LVQ-style classification terms surface in a filing, not as representative of the dataset as a whole.
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 Learning Vector Quantization Prototype Based Classification 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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Reading the numbers
Three figures worth sitting with before treating this set as anything more than a starting point.
Scale
6 families / 19 records
families vs. published records
A small, de-duplicated pool
The search returns 19 published records, which collapse to 6 simple patent families once the same invention filed in multiple countries is merged. Shares and counts elsewhere on this page are given against whichever of these two totals the figure is drawn from.
Counted at retrieval on 2026-10-22.
Filer spread
16.7%
largest single filer's share of 6 families
No filer ahead of the rest
Six filers are tied at 1 family each at the top of the list, and the largest single row, INTELLIGENT INFORMATION SECURITY TECHNOLOGY INC, is named on 1 of the 6 families (16.7%). Filer rows are not rolled up to corporate group and one family can name more than one filer, so these rows cannot be added together into a combined share.
6 listed filers, all organisations; named individuals sit in the totals but not in this list.
Technology split
66.7%
families carrying IPC class G06N
G06N present on most families, not all
G06N (computing based on AI models) is carried by 4 of the 6 families (66.7%); G06F and G06K each appear on 2 of the 6 (33.3%). Because a family can carry several IPC subclasses, these percentages add up to more than 100% and are not a partition of the set.
10 IPC subclasses appear across the dataset in total.
Legal status
37%
records granted and in force, of 19
Status at retrieval, not a success rate
7 of the 19 published records (37%) were granted and still in force at the point of retrieval. The remaining records cover pending, withdrawn, refused, lapsed or otherwise undetermined status, which is not broken down further here.
Legal status changes continuously and is a snapshot, not a measure of quality.
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Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to learning vector quantization prototype based classification patent landscape, with the prior art for and against each one.
Source: Patsnap Eureka. Derived observations on the same dataset. Derived from one Patsnap search for Learning Vector Quantization Prototype Based Classification 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
What's Next
Where to take this from here
This page surfaces the pattern in one search string. Moving from pattern to decision means reading claims directly and testing other phrasings of the same idea.
Read the granted claims
A family count or an abstract cannot establish what a granted claim covers. Pull the claim sets for any family that looks close to a design under consideration before drawing a freedom-to-operate conclusion.
Explore in EurekaTest adjacent phrasings
This search used one specific string. Running variations on prototype-based classification, vector quantization and related terms in Patsnap Eureka can surface families this exact phrasing missed.
Run a new searchTrack the filers found here
The six listed filers are organisations only; named individual filers sit inside the totals but not in this list. Watching filings from these entities over time can flag new activity as it publishes.
Set up monitoringSource: Patsnap Eureka. Suggested next steps. No new data: every figure named here is one of those above. Derived from one Patsnap search for Learning Vector Quantization Prototype Based Classification 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
Questions practitioners ask
A search for learning vector quantization, LVQ or prototype-based terms combined with classification or classifier language returns 19 published records, which de-duplicate to 6 simple patent families once the same invention filed in multiple countries is merged. This is the result of one specific search string with no date limit, not a count of every document that touches LVQ-based classification. A different phrasing of the same idea could return a different set, so treat this figure as a starting point rather than a final tally.
The filer list returned by this search contains 6 organisations, each holding 1 or 2 simple patent families; there is no single filer ahead of the rest, with six entities tied at 1 family apiece at the top of the list. Filer names are not rolled up to corporate group, so a parent and any subsidiary would appear as separate rows if both were present. Named individual inventors are included in the overall totals but are removed from this organisation list, so the rows shown do not represent every filer in the dataset.
Within the 6 families in scope, G06N (computing based on AI models) is the most frequently carried IPC subclass, appearing on 4 of the 6 families (66.7%), followed by G06F (electric digital data processing) and G06K (data recognition and presentation) at 2 families each (33.3%). Because a single family can carry multiple IPC subclasses, these percentages add up to more than 100% and should not be read as a breakdown that sums to the whole set. Ten IPC subclasses appear in total across the dataset, though only the largest few are discussed here.
The filing-trend chart in this dataset is counted in published records by earliest filing year, with a peak so far of 8 records in 2010; the years from 2022 onward are still filling in because publication lags behind filing, sometimes by 18 to 30 months. That incomplete tail means no decline or slowdown can be read into the most recent years shown. With only 6 families in the underlying set, year-to-year movement is too thin to support a trend or maturity judgement either way.
The listed filers include 6 organisations, and the largest single row. Because one family can name more than one filer, these rows overlap and cannot be added together to produce a combined concentration figure; no such sum appears anywhere on this page. With only 6 families in scope, a high or low share for any single row is a function of the small pool size rather than evidence of control over a field.
Answers are grounded in the same dataset. Derived from one Patsnap search for Learning Vector Quantization Prototype Based Classification 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 learning vector quantization prototype based classification 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:(("learning vector quantization" OR LVQ) AND (prototype) AND (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 (G06N) carries 66.7% 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 19 records and 6 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. 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 6 of the 6 filers returned, ordered by count alone; the data endpoint returns at most 100 entities, so even that 6 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 (7 of 19). 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.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company's registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.