R&D and Intellectual Property

Yahoo Japan Corporation (“Yahoo! JAPAN”) of the Z Holdings Group aims to contribute to the development of information technology society. To this end, we promote R&D at Yahoo! JAPAN Research, patent applications according to our intellectual property strategy, and open innovation including the development of OSS (open source software) and others.
In addition, ZOZO Research, the R&D wing of ZOZO Technologies, Inc., undertakes various types of research under its mission, “Quantify Fashion.”

R&D and Intellectual Property Strategy of Yahoo! JAPAN

Supporting Yahoo! JAPAN’s mission of “UPDATE JAPAN” and its aspiration to make Japan more convenient with leading-edge technologies, Yahoo! JAPAN Research works on the research and development of the next-generation of Internet technologies.

In addition, in order to create an environment that constantly produces innovations, we encourage creations through an “Invention Incentive System” to recognize excellent ideas and designs, etc., as well as actively collect and disseminate within and outside the company, information related to advanced technologies and business models of the industry and competitors.
At the same time, in order to ensure fair and free competition, we focus on risk evaluation to respect other companies’ intellectual property rights, while constructing and using an intellectual property portfolio around our own patents and others. The outcome of our R&D as well as our intellectual properties are open to external users in the form of OSS, etc. with which we hope to contribute to the development of an IT society.

About Yahoo! JAPAN Research

Given that various devices are used in different everyday life situations, and the collection of a variety of data continues, Yahoo! JAPAN Research’s goal is value creation leading to next problem-solvings by further deepening our understanding of individuals and trends in the world.

Yahoo! JAPAN Research is broadly collaborating with Yahoo! JAPAN’s service divisions, and several universities and research institutes, in order to achieve maximum results from the valuable environment in which enormous amount of data and feedback from the customers using Yahoo! JAPAN’s services every day are collected daily. Yahoo! JAPAN Research also runs an internship program for students in anticipation of allowing them to use its resources in broadening their research and development activities.
Yahoo! JAPAN Research also has a policy of actively publishing the results of its research and development activities. It not only disseminates the results of joint research performed with universities, but it also recently started providing information about the results of our collaboration with the development teams on Yahoo! JAPAN’s services side.

ZOZO Research – ZOZO’s R&D wing

ZOZO Technologies, Inc., a member of the ZOZO Group, operates an R&D team named “ZOZO research.” The mission of the team is to “quantify fashion.” Leveraging the information asset possessed by the ZOZO Group, it aims to present a scientific answer to the fascinating and puzzling question of fashion: “What does it mean to be ‘beautiful,’ ‘cool,’ and ‘cute’?”

Case in Which Research Led to New Functions in Our Service

Introduction of a ranking model on the constructiveness of news comments

We introduced a ranking model for constructive comments in Yahoo! JAPAN News.

“Irregular Congestion Prediction” function in “Yahoo! JAPAN Transit Navigation” app

A research to “predict” an irregular population density based on the location histories from a few days ago resulted in the “Irregular Congestion Prediction” function that predicts an irregular congestion at stations or trains by 10 minutes.

Certified with “FIDO 2,” a standard that enables safe login through use of biometrics authentication devices, etc.

Yahoo! JAPAN is certified with “FIDO 2,” a new standard established by an industry association called FIDO Alliance, whose mission is to promote the standardization of biometric and other next-generation authentications. We acquired this certification in the world’s first FIDO2 certification test held in August 2018, making us the first FIDO2-certified company in Japan.
This enabled users of Android smartphones to log into Yahoo! JAPAN’s services on web browsers by using biometric authentication, such as fingerprint authentication, from October 2018.

Auto-generation of candidate topic headlines for Yahoo! JAPAN News

We developed a model to auto-generate candidate topic headlines for Yahoo! JAPAN News and introduced it into the editing assistance tool.

Active Communication of Research Results

Yahoo! JAPAN Research actively presents research results at world-leading international conferences etc. (※)

  • ※ Major conferences in 2019
  • •AAAI(Association for the Advancement of Artificial Intelligence): World-leading international conference on artificial intelligence
  • •ACL(Annual Meeting of the Association for Computational Linguistics): One of the world’s largest international conferences in the fields of natural language processing and computational linguistics
  • •CHI(Conference on Human Factors in Computing Systems): Top conference on human-computer interaction (a field that explores designs which enable people to use computers more effectively)
  • •KDD (International Conference on Knowledge Discovery and Data Mining): Top conference in the field of machine learning/data mining

Research Papers by Yahoo! JAPAN Research That Led to Patent Acquisitions

Numerous patents have been obtained from research papers published by Yahoo! JAPAN Research. Please refer to the following;

Year Title of research paper, name of OSS* Classification
2019 Search parameter adjustment
2019 Performance measurement for the specified accuracy range
2019 Time management for building a graph-based index
2019 PredicTaps: Latency Reduction Technique for Single-taps Based on Recognition for Single-tap or Double-tap INTERNATIONAL
2019 ScraTouch: Extending Touch Interaction Technique Using Fingernail on Capacitive Touch Surfaces INTERNATIONAL
2019 Weakly Supervised Multilingual Causality Extraction from Wikipedia DOMESTIC
2019 Real-World Product Deployment of Adaptive Push Notification Scheduling on Smartphones INTERNATIONAL
2019 Simultaneous Detection and Localization of a Wake-Up Word using Multi-Task Learning of the Duration and Endpoint INTERNATIONAL
2019 Parasitic Location Logging: Estimating Users’ Location from Context of Passersby DOMESTIC
2019 Context-Aware Authentication Using Co-Located Devices INTERNATIONAL
2019 incremental skip-gram model with negative sampling
2019 A Case Study on Neural Headline Generation for Editing Support INTERNATIONAL
2019 Dataset Creation for Ranking Constructive News Comments INTERNATIONAL
Papers before 2018
2018 Application of Neural Title Generation as News Editing Assistant (Japanese only) DOMESTIC
2018 Optimization of Indexing Based on k-Nearest Neighbor Graph for Proximity Search in High-dimensional Data INTERNATIONAL
2018 Symbiotic Construction of Individual’s Rich Location Dataset INTERNATIONAL
2018 FIDO Authentication and Its Technology (Japanese only) INTERNATIONAL
2018 Robust ASR against background speech using DNN-mask specializes in wakeup word (Japanese only) DOMESTIC
2018 Continuous Authentication System Using Online Activities INTERNATIONAL
2018 Pretraining Sentiment Classifiers with Unlabeled Dialog Data INTERNATIONAL
2018 Semi-supervised Sentiment Classification with Dialog Data DOMESTIC
2018 Steering through Successive Objects INTERNATIONAL
2017 Identity Verification Using Personal Device’s Context Information(Japanese only) DOMESTIC
2017 Towards authentication using multi-modal online activities INTERNATIONAL
2017 Embedding-based News Recommendation for Millions of Users INTERNATIONAL
2017 AnnexML: Approximate Nearest Neighbor Search for Extreme Multi-label Classification INTERNATIONAL
2017 Extreme Multi-label Learning via k-nearest Neighbor Graph Partitioning(Japanese only) DOMESTIC
2017 Learning Extreme Multi-label Tree-classifier via Nearest Neighbor Graph Partitioning INTERNATIONAL
2016 Quantifying Query Ambiguity with Topic Distributions INTERNATIONAL
2016 Pruned Bi-directed K-nearest Neighbor Graph for Proximity Search INTERNATIONAL
2016 big3store INTERNATIONAL
2016 Ensure User Identity by Using Biometrics(Japanese only) DOMESTIC
2016 Multimodal Content-Aware Image Thumbnailing INTERNATIONAL
2016 Quantifying Query Ambiguity with Topic Distributions(Japanese only) DOMESTIC
2015 The Optimization of Budget Consumption for Internet Targeting Ads.(Japanese only) DOMESTIC
2015 The Agitation Detection in Stock Bulletin Board(Japanese only) DOMESTIC
2014 A Distributed Query Execution Method for RDF Storage Managers INTERNATIONAL
2014 Filling Context-Ad Vocabulary Gaps with Click Logs INTERNATIONAL
2014 Translation Method of Contextual Information into Textual Space of Advertisements INTERNATIONAL
2013 Applying a Graph-Structured Index to Product Image Search(Japanese only) DOMESTIC
2013 Extendable Dialog Script Description Language for Natural Language User Interfaces INTERNATIONAL
2013 Primitive Operation Aggregation Algorithms for Improving Taxonomies for Large-Scale Hierarchical Classifiers INTERNATIONAL
2012 Toward personal experience management in a socially networked world INTERNATIONAL
2012 Organization and exploration of heterogeneous personal data collected in daily life INTERNATIONAL
2012 Policy Provisioning and Its Access Control Beyond Administrative and Collaborative Domains INTERNATIONAL
2012 Authentication Trust Metric and Assessment for Federated Identity Management Systems INTERNATIONAL
2011 Access Control Model and Design for Delegation Using Authorization Tokens INTERNATIONAL
2011 Establishing Authentication Trust in Open Environment Using Social Approach INTERNATIONAL
2011 Dynamic Identity Delegation Using Access Tokens in Federated Environments INTERNATIONAL
2011 Data and Access Management Using Access Tokens for Delegating Authority to Persons and Software INTERNATIONAL
2011 Proximity Search using Approximate K Nearest Neighbor Graph with a Tree Structured Index(Japanese only) DOMESTIC
2010 Policy Provisioning for Distributed Identity Management Systems INTERNATIONAL
2010 Improving Taxonomies for Large-Scale Hierarchical Classifiers of Web Documents INTERNATIONAL
2010 Tag Clouds in the Cloud: A Visual Interface for the Display of Tag Clusters(Japanese only) DOMESTIC
2010 An Authentication Trust Metric for Federated Identity Management Systems INTERNATIONAL
2010 A Persistent Data Tracking Mechanism for User-centric Identity Governance INTERNATIONAL
2010 Doughnut Crumbs:Visual Navigation for Data Hierarchies INTERNATIONAL
2010 Proximity Search in Metric Spaces Using Approximate K Nearest Neighbor Graph(Japanese only) DOMESTIC
2009 User-Centric Identity Governance across Domain Boundaries INTERNATIONAL
2009 Identity Information Exchange and Control with Access Token(Japanese only) DOMESTIC
2009 Web contents navigation guided by surrounding information and navigation route(Japanese only) DOMESTIC
2008 Building an Autopoietic Knowledge Structure for Natural Language Conversational Agents INTERNATIONAL
2008 Determination of importance of phrases included in a product title using statistical information of “shopping category” and “handling store”(Japanese only) DOMESTIC
  • *Linked to the webpage of Yahoo Japan Corporation

Patent Portfolio

Using the Patent Score (※), the diagram demonstrates the total strength of each company’s patent asset on the vertical axis evaluated from the quality and quantity of patent assets possessed, and the individual strength of the most valuable patent of each company on the horizontal axis. The sizes of circles represent the number of patents each company has. Yahoo! JAPAN favorably compares with other world-leading companies in terms of domestic patents on the whole. Yahoo! JAPAN particularly has a strong position in the field of e-commerce, which is one of its focus areas.

  • ※ Patent Score is an indicator of the degree of attention being paid to each patent. In other words, “a high-profile patent has a high Patent Score,” and “a low-profile patent has a low Patent Score.” Source: Patent Result Co., Ltd.
patent portfolio
E-commerce(ads & e-commerce)

Patent Asset Ranking

Patent asset ranking is a ranking that comprehensively evaluates each company’s patents in terms of both quality and quantity, using the Patent Score. Yahoo! JAPAN placed second in the category of patents’ total strength in “Patent Asset Ranking for the Information-communication Industry 2019” published by Patent Result Co., Ltd.
Among the high-profile patents of Yahoo! JAPAN are “Advertising in navigation systems” and “Display program for enhanced ad content visibility in Internet advertising.”

Name of company
Size of patent asset (pt)
No. of patents
2Yahoo! JAPAN
6XIAOMI (China)
9Rakuten, Inc.
10Konami Digital Entertainment Co., Ltd.
  • Top 10 companies in the information-communication industry (source: Patent Result)

Transition in the Number of Domestic Patent Applications

Yahoo! JAPAN started the current Invention Incentives and Award Program in 2014. Ever since, the number of patent applications by Yahoo! JAPAN is increasing every year. In recent years, Yahoo! JAPAN promotes the utilization of its multi big data, which is its strength.
Yahoo! JAPAN makes an all-out effort to conduct R&D in the field of data science, which supports utilization of data, as well as to improve services utilizing data. It also actively makes patent applications in order to protect these research results with patent rights and to capitalize them.

Transition in the number of patent applications by Yahoo Japan Corporation FY2000:49, FY2012:268 , FY2013:249, FY2014:234, FY2015:340, FY2016:445, FY2017:635, FY2018:550 FY2019:298

Promoting Open Innovations

In order to contribute to the development of the information technology society, Yahoo! JAPAN Research’s development results and intellectual properties created in Yahoo! JAPAN are made available to the public in the form of OSS, etc. Many of them are being utilized in various situations. We believe that encouraging to create a healthy market will also lead to the future development of Yahoo! JAPAN.

OSS of AI technology that reduces learning time of distributed representation

“yskip”, an AI/natural language processing technology that reduces the learning time of distributed representation, is made available as an OSS. This technology is used in matching information of users’ interest with articles and advertisements by machine-learning the relationship between various words from a vast amount of text data and automatically estimating the differences in the meanings of words.

OSS developer certification program

This is a program that certifies selected employees as developers for OSS which is strategically adopted by Yahoo! JAPAN. Time used for developing specific OSS is regarded as work hours and a maximum of JPY 1 million budget per year is granted for the certified employees to work as OSS committers.

NGT(Neighborhood Graph and Tree for Indexing)

NGT is an OSS developed by Yahoo! JAPAN. This is a software that allows users to quickly search and identify data with multiple characteristics (high-dimensional data), such as text, image, product/user data from a large database. NGT won IPSJ Industrial Achievement Award 2019 from Information Processing Society of Japan.

Collaborations with External Partners

Yahoo! JAPAN, a member of the Z Holdings Group, collaborates with external partners from diverse fields, including enterprises, universities, and research institutions, to make our users’ life more convenient and more enriching. We also aim to solve various social problems through these collaborative initiatives.

Yahoo! JAPAN Research and Anicom jointly announce study findings on connection between pet food and allergies

Making combined use of the insurance claim data and questionnaire results possessed by Anicom Insurance, Inc., and Yahoo! JAPAN’s e-commerce data on pet food purchases, we conduct analyses and validation of the suspected connection between pet food ingredients and allergies.

ZOZO Inc. launches joint research with Yale University to apply economics to understanding of customer incentives and behavioral psychology and optimization of customer communication

The objective of this joint research is to understand customer incentives and psychology behind their purchasing behavior and to optimize communications tailored for each user, utilizing both the expertise of Dr. Kosuke Uetake, Associate Professor of Marketing, Yale School of Management, who specializes in quantitative marketing and empirical industrial organization, and ZOZOTOWN’s large-scale and diverse data. Through this initiative, we aim to further enhance our services in ZOZOTOWN, and in the long run, to maximize the value of use customer lifetime value for ZOZOTOWN users.

SEIBU RAILWAY Co., Ltd. and Yahoo! JAPAN conduct demonstration experiment using big data and AI for prediction of train congestion

The congestion pattern of each station is projected thorough AI (machine learning)-powered analytics of big data collected from the Yahoo! JAPAN Transit Navigation service; the data utilized includes search histories of future train/transit schedules, and is pre-processed into anonymized statistical data (removing personal identifiers). Combining this with the SEIBU RAILWAY’s data on the number of people getting off the train by stations and by time, we aim to realize even more accurate congestion prediction.

Yahoo! JAPAN conducts demonstration experiments for AI-powered big data collaboration between companies

Yahoo! JAPAN has conducted demonstration experiments with various companies and municipalities, including Nissan Motor Co., Ltd., Ezaki Glico Co., Ltd., Japan Professional Football League, Kobe City, and Fukuoka City, for AI-powered big data collaboration between organizations.

Yahoo! JAPAN conducts joint demonstration experiment with Tokyo Metropolitan Government for prevention of heatstroke using AI

Yahoo! JAPAN conducted a joint demonstration experiment with the Tokyo Metropolitan Government for predicting heatstroke risks at crowded places such as event venues, with high accuracy. In the experiment, the WBGT (wet bulb globe temperature; heat stress index) open data released by the Ministry of Environment for the purpose of preventing heatstrokes was combined with the congestion information derived by Yahoo! JAPAN using its big data on location information. Congestion is considered to be one of the factors pushing up the heat stress index, and the heatstroke risks were predicted through the AI-powered analytics of the combined big data.