Philip K. Yu - Rowland Heights CA, US Calvin C. Fang - Rowland Heights CA, US
International Classification:
G08L019/00 H04M001/00 H04M003/00 H04B001/38
US Classification:
34082569, 455563, 4555611, 455418, 4555561
Abstract:
An improved universal remote control unit (URC) for home entertainment units. The URC has the typical remote controller module for controlling appliances such as TV, stereo, VCR or DVD. Additionally, the URC has a built-in digital recorder module for recording the consumer's voice, or any audio messages from the appliances. The digital recorder module can be implemented with a microphone, a voice recorder chip and a speaker, all integrated with the URC unit. The digital recorder module can even use the battery that is typically used by the URC. The URC alternatively can be implemented with a memory and display screen, coupled to the number keys. Such arrangement allows the telephone information to be punched in, using the numeric keys on the URC, stored in the memory for display.
Method Of Using The Internet To Retrieve And Handle Articles In Electronic Form From Printed Publication Which Have Been Printed In Paper Form For Circulation By The Publisher
A method and system of using the Internet to retrieve printed articles from printed media. The method of the present invention first tags each printed article that is to be published in print. The tag is also printed with the printed article to allow readers to identify. The printed article and its tag are collected and stored in a database, which is accessible through the Internet or the Worldwide Web. When a reader finds a printed article of interest to the reader on the print version of the media, the reader sends a request with the tag to the database. Upon receiving the request and the tag, the database is searched to locate the printed article. Upon locating the stored printed article in the database, it is transmitted to the reader's computer or to the reader's email address. Such article can now be stored, filed, distributed, shared in anyway the reader sees fit, all without having to labor through the traditional manual clipping tasks. Additionally, each retrieval of the printed article is bundled with additional information that is relevant to the printed article.
Universal Remote Controller With Voice And Digital Memory
An improved universal remote control unit (URC) for controlling electronic appliance units. The URC unit has the typical remote controller module for controlling appliances such as TV, stereo, VCR or DVD. Additionally, the URC has a scratch pad memory for storing telephone numbers and web site information entered through the URC unit's alphanumeric keys. When activated, the key pad entries are stored in the memory, instead of being used to control the appliance. The URC unit further has a digital recorder module that can be implemented with a microphone, a voice recorder chip and a speaker, all integrated with the URC unit. The digital recorder module can even use the battery that is typically used by the URC unit. The URC unit further has a display screen to display the information stored in and recalled from the memory.
System And Method For Load Shedding In Data Mining And Knowledge Discovery From Stream Data
Yun Chi - Los Angeles CA, US Haixun Wang - Irvington NY, US Philip S. Yu - Chappaqua NY, US
Assignee:
International Business Machines Corporation - Armonk NY
International Classification:
G06F 12/00 G06F 17/30 G06F 9/46
US Classification:
707200, 718104, 718105
Abstract:
Load shedding schemes for mining data streams. A scoring function is used to rank the importance of stream elements, and those elements with high importance are investigated. In the context of not knowing the exact feature values of a data stream, the use of a Markov model is proposed herein for predicting the feature distribution of a data stream. Based on the predicted feature distribution, one can make classification decisions to maximize the expected benefits. In addition, there is proposed herein the employment of a quality of decision (QoD) metric to measure the level of uncertainty in decisions and to guide load shedding. A load shedding scheme such as presented herein assigns available resources to multiple data streams to maximize the quality of classification decisions. Furthermore, such a load shedding scheme is able to learn and adapt to changing data characteristics in the data streams.
Systems And Methods For Maintaining Closed Frequent Itemsets Over A Data Stream Sliding Window
Yun Chi - Los Angeles CA, US Haixun Wang - Irvington NY, US Philip S. Yu - Chappaqua NY, US
Assignee:
International Business Machines Corporation - Armonk NY
International Classification:
G06F 17/00
US Classification:
707102, 345660
Abstract:
Towards mining closed frequent itemsets over a sliding window using limited memory space, a synopsis data structure to monitor transactions in the sliding window so that one can output the current closed frequent itemsets at any time. Due to time and memory constraints, the synopsis data structure cannot monitor all possible itemsets, but monitoring only frequent itemsets makes it difficult to detect new itemsets when they become frequent. Herein, there is introduced a compact data structure, the closed enumeration tree (CET), to maintain a dynamically selected set of itemsets over a sliding-window. The selected itemsets include a boundary between closed frequent itemsets and the rest of the itemsets Because the boundary is relatively stable, the cost of mining closed frequent itemsets over a sliding window is dramatically reduced to that of mining transactions that can possibly cause boundary movements in the CET.
System And Method For Load Shedding In Data Mining And Knowledge Discovery From Stream Data
Yun Chi - Los Angeles CA, US Haixun Wang - Irvington NY, US Philip S. Yu - Chappaqua NY, US
Assignee:
International Business Machines Corporation - Armonk NY
International Classification:
G06F 7/00 G06F 17/00
US Classification:
707603, 706 46, 718104, 718105
Abstract:
Load shedding schemes for mining data streams. A scoring function is used to rank the importance of stream elements, and those elements with high importance are investigated. In the context of not knowing the exact feature values of a data stream, the use of a Markov model is proposed herein for predicting the feature distribution of a data stream. Based on the predicted feature distribution, one can make classification decisions to maximize the expected benefits. In addition, there is proposed herein the employment of a quality of decision (QoD) metric to measure the level of uncertainty in decisions and to guide load shedding. A load shedding scheme such as presented herein assigns available resources to multiple data streams to maximize the quality of classification decisions. Furthermore, such a load shedding scheme is able to learn and adapt to changing data characteristics in the data streams.
Indianapolis, Indiana, USAProduct Line Manager at JDSU Past: International Product Marketing Manager at JDSU, Staff Software Engineer at JDSU, Senior... International Product Marketing Manager
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University of Washington - Applied and Computational Mathematical Sciences: Discrete Math and Algorithms, South Puget Sound Community College - Associate of Science