権利抹消識別 (JP)

Import numbers

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Close

Save the numbers on the server

Rank	Score	AI predict score	Application	Publication	Examined/Granted
{{numberRank.rank}}	{{numberRank.score}}	{{numberRank.predict_score}}	{{numberRank.app_id}}	{{numberRank.pub_id}}	{{numberRank.exam_id}}

Search conditions

Save search condition

Email Alert

Set saved search conditions

{{ preCondition.lop }} {{preUserSearchSettings[preCondition.q][0]}} {{preUserSearchSettings[preCondition.q][1] ? '(' + preUserSearchSettings[preCondition.q][1] + ')' : ''}} {{preCondition.key}}

Delete All

Save search condition

Search conditions

Name {{userSearchSetting.title}}

Default

Email Alert

Disable Zero Alert

Period

Latest published

Latest granted

New Update

Load from the saved search conditions

Created at : {{userSearchSetting.created_at | strftime('YYYY-MM-DD')}}
N hits on last searched : {{userSearchSetting.last_searched_n_hits}}

Remove the saved search conditions

Save

{{query[1]}} Search | Delete

{{query[0]}}

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More

Reset

More

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More

N records
N clusters
N search words

# of cited

# of citing

Max # of connection

End edge only

Remove citation sources

Exclude same with

Include same with

Get Citation Type Cited/Citing Auto

+ Add filter conditions

Logical expression

フィルター行番号(L:N)を組み合わせて論理式を設定できます。例： (L:1 OR L:2) AND L:3

Predict model

Select the work group :

Predict model (Pre) :

Label type

Binary class Multi class Multi label

Targe features

Custom Labels

{{labelName.name}} {{countLabelName(labelName.name)}} {{labelName.weight ? labelName.weight : '1.0'}}

{{labelName.name}} {{countLabelName(labelName.name)}} {{labelName.weight ? labelName.weight : '1.0'}}

Supervised labels Prediction labels Visualize Parameter tuning Option

Pupervised labels Prediction labels Visualize Parameter tuning Option

Manual Update

Adjust score with AI prediction score

Enable prediction with search results

Enable semantic score

# of predict labels

Using data for tuning A part of train data Predict data

Ratio of tuning

Features for tuning

C : Cost

Sigma : Kernel parameter

Prefer label(binary)

Evaluation

Best parameters
Accuracy : {{Math.floor((tuningBest.accuracy * 1000)) / 1000}} Precision : {{Math.floor((tuningBest.precision * 1000)) / 1000}} Recall : {{Math.floor((tuningBest.recall * 1000)) / 1000}} Fmeature : {{Math.floor((tuningBest.fmeasure * 1000)) / 1000}} Targe features : {{t.supervised_label_sets[tuningBest.features]}} C: {{tuningBest.c}} Sigma: {{tuningBest.sigma}} Prefer label(binary) : {{tuningBest.force_zero}}

Precision : {{Math.floor((result.accuracy * 1000)) / 1000}} Precision : {{Math.floor((result.precision * 1000)) / 1000}} Recall : {{Math.floor((result.recall * 1000)) / 1000}} Fmeature : {{Math.floor((result.fmeasure * 1000)) / 1000}} Targe features : {{t.supervised_label_sets[result.features]}} C: {{result.c}} Sigma: {{result.sigma}} Prefer label(binary) : {{result.force_zero}}

Query type

Query Empty query Query must be less than 1000 characters Already exists Invalid number Too many supervised labels Too many prediction labels

Label

Pupervised labels Import from file Save supervised labels Edit supervised labels Save supervised labels CSV DL Delete All Parameter Settings Manual

Prediction labels Import from file Save prediction labels Edit prediction labels Save prediction labels CSV DL Delete All Parameter Settings Manual

C : Cost

Sigma : Kernel parameter

Prefer label(binary)

Automatically parameters tuning

Target of import

# of import

Import

Choose file / Drag & Drop

No supervised labels

{{trainPageStart+index+1}} App Pub Exam {{label.q}} {{label.q}} {{label.n ? label.n : ' '}} {{label}} {{label}} {{label.s.join(',')}} {{label.l}}

- Accuracy : {{Math.floor((trainAccuracy * 1000)) / 1000}} Precision : {{Math.floor((trainPrecision * 1000)) / 1000}} Recall : {{Math.floor((trainRecall * 1000)) / 1000}} F-measure : {{Math.floor((trainFMeasure * 1000)) / 1000}}

Choose file / Drag & Drop

No prediction labels

{{predictPageStart+index+1}} App Pub Exam {{label.q}} {{label.q}} {{label.n ? label.n : ' '}} {{Math.floor((label.ps * 1000)) / 1000}} {{Math.floor((label.ps * 1000)) / 1000}} {{label.pcs.join(',')}} {{label.pl}} {{label}} {{label}} {{label.s.join(',')}} {{label.l}}

Accuracy : {{Math.floor((accuracy * 1000)) / 1000}} ({{correct}} / {{total}}) Precision : {{Math.floor((precision * 1000)) / 1000}} Recall : {{Math.floor((recall * 1000)) / 1000}} F-measure : {{Math.floor((FMeasure * 1000)) / 1000}}

{{labelName.name}} : {{Math.floor((predictStats[labelName.name].correct / predictStats[labelName.name].total) * 1000) / 1000}} ({{predictStats[labelName.name].correct}} / {{predictStats[labelName.name].total}})

Train Label filter

Custom Label filter

Custom Pre Label filter

Data reference > 権利抹消識別 (JP)

コード	説明
0	本権利は抹消されていない
1	年金不納による抹消
12	登録後の権利抹消（その他）
15	付与後異議による抹消
2	存続期間満了による抹消
3	放棄による抹消
4	無効審判の確定による抹消
7	猶予の特許・登録料不納による抹消
99	出願から25年以上経過済で抹消フラグが不明のもの

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Display settings

AI label settings

Supervised labels Prediction labels Visualize Parameter tuning Option

Pupervised labels Prediction labels Visualize Parameter tuning Option

Pupervised labels Prediction labels Visualize Parameter tuning Option

Pupervised labels Prediction labels Visualize Parameter tuning Option

Pupervised labels Prediction labels Visualize Parameter tuning Option

Pupervised labels Import from file Save supervised labels Edit supervised labels Save supervised labels CSV DL Delete All Parameter Settings Manual

Prediction labels Import from file Save prediction labels Edit prediction labels Save prediction labels CSV DL Delete All Parameter Settings Manual

権利抹消識別 (JP)

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