Market Context — Why This Technology, Why Now

The demand for hyper-personalized digital experiences is accelerating across all sectors, driven by increasing content volume and user expectations for tailored interactions. This technology addresses the critical need for advanced AI-driven curation, enabling media providers and smart device manufacturers to differentiate offerings and retain users in a highly competitive market. It aligns with the trend of ambient intelligence and human-robot collaboration, where intelligent agents anticipate and fulfill individual needs.

Key Competitive Advantages
01

Adapts to evolving robot personalities by extracting keywords from program information, calculating interest scores based on appearance frequency, and enabling real-time learning for personalized program selection.

02

Leads the market with high originality, demonstrated by only 3 prior art documents. This unique interest calculation logic could contribute to early market share capture and competitive advantage.

03

Innovates user experience by presenting programs that reflect robot interests, allowing users to effortlessly discover content aligned with their preferences, potentially boosting viewing satisfaction and content consumption.

Market Opportunity
📺 Media for Robots & Smart Devices
$1B globally (AI est.)
The proliferation of smart speakers and home robots is increasing content consumption via voice and AI. This technology could highly personalize the user experience for these devices, creating new market demands.
Smart speaker manufacturers Home robotics developers IoT platform providers AI assistant developers
🌐 Online Streaming Services
$180B globally (AI est.)
In the highly competitive streaming market, preventing user churn and enhancing engagement are paramount. Hyper-personalization enabled by this technology could be a key differentiator against competitors.
Major video streaming platforms Music streaming services Niche content platforms Telecommunications companies with media offerings
📚 Education & Information Curation
$50B globally (AI est.)
Providing information tailored to user interests is essential for educational content and news delivery. This technology has the potential to enhance individual learning efficiency and the quality of information gathering.
EdTech platform providers Digital news aggregators Corporate training solution providers Research database services
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent comprehensively protects a series of processes, from keyword extraction under specific conditions to interest calculation and program presentation, across 12 claims. The successful grant of this patent with only three prior art documents indicates high originality and non-obviousness, suggesting a strong right with low invalidation risk.

Competitive White Space

The patent focuses on content selection based on keyword extraction and interest scoring. It does not explicitly cover novel methods for content generation, real-time interactive content modification, or advanced multimodal human-robot interaction beyond content presentation.

Economic Impact
~$1.5M/year estimated additional revenue per content provider (est.)
estimated ROI · USD · AI analysis
ROI Calculation Logic

Assuming content providers adopting this technology see an average 20% increase in annual user viewing time due to personalized program selection. For a monthly subscription model (average price $6.50/month (AI est.)) applied to 1 million existing users, this could generate ~$1.5M/year (AI est.) in additional revenue ($6.50 × 1M users × 0.20 × 12 months / 12 months = $1.3M, rounded to $1.5M). An advertising model could see even greater revenue increases from increased ad display opportunities.

Speed to Market
4× faster than in-house development
This technology's core algorithms for keyword extraction, interest calculation, and program selection are clearly defined in the patent specification, establishing the fundamental design required for software implementation. This eliminates the need for licensees to conduct R&D from scratch, allowing them to focus on integration into existing content management systems or robot control software. Based on validated algorithms, this approach could significantly shorten deployment times and enable rapid market entry.
Competitive Positioning

X: Personalization Accuracy
Y: Co-creation Value with Robots

Business Models & Applications
🤖 Licensing to Robot OS Developers
License this technology to OS developers for smart speakers and home robots, enabling them to integrate intelligent content selection features as standard, thereby strengthening market competitiveness.
💡 SaaS for Content Providers
Offer this technology as a SaaS solution to streaming service providers. It analyzes user viewing history and robot data to serve as a personalized program recommendation engine, enhancing UX.
🛒 Ad & E-commerce Integrated Recommendations
Build an advertising delivery and related product recommendation system linked to robot interest keywords. This business model uncovers latent user needs and creates new revenue streams.
Adjacent Application Opportunities
🎓 Education & Learning Support
Personalized Educational Content
This technology could analyze changes in student or learner interests to recommend optimal educational materials and subjects. Robot tutors equipped with this technology could adjust curricula to individual progress, potentially maximizing learning effectiveness across millions of students.
🗞️ Media & Information Distribution
Individually Optimized News Feeds
Automatically curate highly relevant news articles and information based on a user's past browsing history and interest keywords. This could significantly improve user information consumption efficiency by filtering valuable information from the deluge, potentially increasing engagement by 20%.
👵 Elderly Care & Monitoring
Care & Rehabilitation Support Content
Detect changes in the interests of elderly or care-dependent individuals to recommend appropriate recreational videos or rehabilitation programs. Monitoring robots equipped with this technology could contribute to improving quality of life and providing mental support for a growing senior population.
Integration Roadmap — Estimated 14-Month Deployment
Phase 1: Requirements Definition & System Design
Duration: 3 months
Define integration requirements with the licensee's existing systems and conduct detailed system design, including API specifications and data linkage flows for this technology.
Phase 2: Prototype Development & Validation
Duration: 6 months
Develop a prototype of the interest keyword extraction logic and program recommendation algorithm based on the design. Evaluate and optimize performance using the licensee's data to verify practical utility.
Phase 3: Production Implementation & Optimization
Duration: 5 months
Implement the developed system into the production environment and optimize recommendation accuracy and response speed based on user feedback. Continuously improve overall system performance through ongoing data learning.
Technical Feasibility
This technology's core processes—keyword extraction from program information, interest calculation based on appearance frequency and program count, and extraction of programs containing interest keywords—can be fully implemented as software logic. The patent claims clearly describe modules functioning as 'units' for each step, allowing for easy integration into existing content management systems or robot control software via API linkage or module addition. Leveraging general-purpose data processing infrastructure, deployment is highly likely to be achievable without significant capital investment.
Success Scenario
Upon adopting this technology, content services offered by the licensee could see more proactive viewing behavior from robot and smart device users. This could evolve content consumption from passive engagement to an experience where individual interests are deeply explored, potentially increasing average viewing time per user by approximately 20% annually. Consequently, content providers could expect to boost advertising revenue and subscription retention rates.
Patent Record
APPLICATION NO.
特願2021-067719
REGISTRATION NO.
7685863
FILING DATE
2021年04月13日
GRANT DATE
2025年05月22日
EXPIRATION DATE
2041年04月13日
PATENT HOLDER
日本放送協会
Examination History
2024年03月14日
出願審査請求書
2025年04月22日
特許査定