{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-9854220","patent":{"patent_number":"US-9854220","title":"Information processing apparatus, program, and information processing method","assignee":null,"inventors":[],"filing_date":"2013-05-02T00:00:00.000Z","publication_date":"2017-12-26T00:00:00.000Z","cpc_codes":["H04N","H04N","H04N","H04N","H04N","H04N","H04N"],"num_claims":9,"abstract":"An information processing apparatus includes a content reproduction unit, a content part specification unit, a clustering unit, a class detection unit, a common class extraction unit, and a content retrieval unit. The content reproduction unit is configured to reproduce a reproduction content. The content part specification unit is configured to specify a plurality of content parts included in the reproduction content. The clustering unit is configured to classify the plurality of content parts into a plurality of clusters. The class detection unit is configured to detect a class from the plurality of content parts included in each of the plurality of clusters. The common class extraction unit is configured to extract a common class common to the plurality of clusters from the classes detected by the class detection unit. The content retrieval unit is configured to retrieve a content corresponding to the common class."},"analysis":{"summary":"The Information Processing Apparatus, Program, and Information Processing Method patent introduces a system designed to enhance content retrieval by intelligently analyzing and classifying content parts within a reproduction. The core innovation lies in its ability to identify common themes across various content clusters, enabling the system to retrieve highly relevant content tailored to user interests. This patent addresses the problem of information overload by providing a more efficient and targeted approach to content discovery.\n\nThe key technical approach involves a multi-stage process. First, a content reproduction unit reproduces the content. Then, a content part specification unit identifies and segments the content into distinct parts. Next, a clustering unit groups these parts into clusters based on similarity. A class detection unit then identifies the dominant classes within each cluster. The common class extraction unit distills these classes to find commonalities across multiple clusters. Finally, the content retrieval unit leverages these common classes to retrieve related content.\n\nThe business value of this technology is significant. It can improve user engagement, increase content consumption, and drive revenue growth. By providing more relevant and targeted content, businesses can keep users engaged for longer periods of time. This can lead to increased advertising revenue, subscription sales, and other forms of monetization. The market opportunity is vast, spanning industries such as media streaming, e-learning, and online advertising. \n\nThis technology enables content providers to offer more personalized and engaging experiences, creating a competitive advantage in the crowded digital landscape. The system's ability to adapt to changing user preferences further enhances its value, ensuring that content suggestions remain relevant over time. This innovation represents a significant step forward in the field of content retrieval and has the potential to transform the way we consume and interact with information.","layman_explanation":"The Information Processing Apparatus, Program, and Information Processing Method patent addresses a significant problem in today's digital world: the overwhelming amount of content available. It's become increasingly difficult to find the specific information or entertainment we're looking for amidst the vast sea of online data. This technology offers a solution by intelligently organizing and filtering content to provide users with more relevant and personalized results.\n\n**What Problem Does This Solve?**\nImagine trying to find a specific scene in a movie or a particular topic in a lengthy document. Current search methods often fall short, returning a jumble of results that require significant time and effort to sift through. This patent aims to eliminate that frustration by creating a system that understands the content and your preferences, delivering only the most relevant options.\n\n**How Does It Work?**\nThink of it like a librarian who not only knows every book in the library but also understands your reading habits. The system first breaks down the content into smaller parts, like scenes in a movie or paragraphs in a document. It then groups these parts into categories based on their similarity. Finally, it identifies the categories that are most relevant to your interests and presents you with content from those categories. Instead of searching through the entire library, you're directed straight to the section that contains exactly what you're looking for.\n\n**Why Does This Matter?**\nThis technology has the potential to revolutionize how we consume information and entertainment. It can save us time, reduce frustration, and enhance our overall experience. For businesses, it offers the opportunity to provide more personalized and engaging experiences to their customers, leading to increased satisfaction and loyalty. The market impact could be substantial, with applications ranging from streaming services to e-learning platforms.\n\n**What's Next?**\nAs the amount of digital content continues to grow, the need for intelligent organization and filtering will only become more pressing. This patent lays the foundation for future innovations in content retrieval and personalization. We can expect to see further advancements in this area, driven by the increasing power of artificial intelligence and machine learning. The potential applications are vast, and the market opportunity is significant.","technical_analysis":"The Information Processing Apparatus, Program, and Information Processing Method patent outlines a sophisticated system for content retrieval based on intelligent analysis and classification of content parts. The system's architecture comprises several key modules: a content reproduction unit, a content part specification unit, a clustering unit, a class detection unit, a common class extraction unit, and a content retrieval unit. Each unit performs a specific function, contributing to the overall goal of efficient and targeted content retrieval.\n\nThe content reproduction unit is responsible for reproducing the content, which can be in various formats such as text, audio, or video. The content part specification unit then identifies and segments the content into distinct parts, enabling granular analysis. This segmentation process is crucial for the subsequent clustering and classification steps. The clustering unit groups the content parts into clusters based on similarity metrics. Various clustering algorithms can be employed, such as k-means, hierarchical clustering, or DBSCAN, depending on the specific application and data characteristics.\n\nThe class detection unit identifies the dominant classes within each cluster. This can be achieved using techniques such as frequency analysis or machine learning classifiers. The common class extraction unit then distills these classes to find commonalities across multiple clusters, highlighting the most relevant themes. Finally, the content retrieval unit leverages these common classes to retrieve related content from a database or other content repository.\n\nThe implementation of this technology requires careful consideration of several factors. The choice of clustering algorithm and classification techniques is critical for achieving optimal performance. The system must also be able to handle large volumes of data efficiently. Furthermore, the system should be designed to adapt to changing user preferences and content patterns. The Information Processing Apparatus, Program, and Information Processing Method presents a robust and scalable approach to content retrieval, with potential applications in various industries.","business_analysis":"The Information Processing Apparatus, Program, and Information Processing Method patent presents a significant business opportunity in the rapidly evolving landscape of digital content. The market for content recommendation and personalization is growing rapidly, driven by the increasing volume of digital content and the need for more efficient and targeted content delivery. This patent addresses this need by providing a system that can intelligently analyze and classify content parts, thereby facilitating more efficient and personalized content retrieval.\n\nThe market opportunity size is substantial. Industries such as media streaming, e-learning, and online advertising are all facing the challenge of content overload. The Information Processing Apparatus, Program, and Information Processing Method can help these industries improve user engagement, increase content consumption, and drive revenue growth. The competitive advantages of this technology include its ability to intelligently analyze and classify content parts, its adaptability to changing user preferences, and its scalability to handle large volumes of data.\n\nThe revenue potential of this technology is significant. Content providers can offer premium services that provide users with access to highly curated and personalized content experiences. This can be a significant differentiator in a crowded marketplace. The business model can be based on subscription fees, advertising revenue, or a combination of both. The strategic positioning of this technology is also favorable. It aligns with the growing trend towards personalization and the increasing demand for more efficient content retrieval methods.\n\nThe ROI projections for this technology are promising. By improving user engagement and increasing content consumption, businesses can generate significant revenue growth. The cost of implementing this technology can be offset by the increased revenue and improved user satisfaction. The Information Processing Apparatus, Program, and Information Processing Method represents a compelling investment opportunity in the field of content recommendation and personalization.","faqs":null,"topics":["content retrieval","information processing","content classification","clustering","machine learning"],"tech_cluster":null},"seo":{"title":"Information Processing Apparatus, Program, and Information Processing Method - Patent US-9854220","description":"Discover how this patent enhances content retrieval by intelligently analyzing and classifying content parts. Full patent analysis, claims, and technical details.","keywords":["content retrieval","information processing","content classification","clustering","machine learning","content recommendation","patent","patent US-9854220"]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-9854220","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-9854220","citation_suggestion":"Patentable. \"Information processing apparatus, program, and information processing method\" (US-9854220). https://patentable.app/patents/US-9854220","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-9854220","json":"https://patentable.app/api/llm-context/US-9854220","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T05:10:31.745Z"}