Jason Eisner

US Patent:

RE41152, Feb 23, 2010

Filed:

Sep 14, 2001

Appl. No.:

09/952602

Inventors:

Jeffrey C. Reynar - Woodinville WA, US
Fred Herz - Milton WV, US
Jason Eisner - Baltimore MD, US
Lyle Ungar - Philadelphia PA, US

Assignee:

Pinpoint Incorporated - Forth Worth TX

International Classification:

G06F 7/00
G06F 15/00
H03M 7/00

US Classification:

708203, 708212, 341 50, 341 51, 341 87, 341 95, 341106, 35842601, 380217

Abstract:

An adaptive compression technique which is an improvement to Lempel-Ziv (LZ) compression techniques, both as applied for purposes of reducing required storage space and for reducing the transmission time associated with transferring data from point to point. Pre-filled compression dictionaries are utilized to address the problem with prior Lempel-Ziv techniques in which the compression software starts with an empty compression dictionary, whereby little compression is achieved until the dictionary has been filled with sequences common in the data being compressed. In accordance with the invention, the compression dictionary is pre-filled, prior to the beginning of the data compression, with letter sequences, words and/or phrases frequent in the domain from which the data being compressed is drawn. The letter sequences, words, and/or phrases used in the pre-filled compression dictionary may be determined by statistically sampling text data from the same genre of text. Multiple pre-filled dictionaries may be utilized by the compression software at the beginning of the compression process, where the most appropriate dictionary for maximum compression is identified and used to compress the current data.

US Patent:

8285619, Oct 9, 2012

Filed:

Jan 22, 2002

Appl. No.:

10/054057

Inventors:

Frederick S. M. Herz - Warrington PA, US
Lyle H. Ungar - Philadelphia PA, US
Jason M. Eisner - Baltimore MD, US
Walter Paul Labys - Ogden UT, US

Assignee:

Fred Herz Patents, LLC - Milton WV

International Classification:

G06Q 40/00

US Classification:

705 36R

Abstract:

A method of using natural language processing (NLP) techniques to extract information from online news feeds and then using the information so extracted to predict changes in stock prices or volatilities. These predictions can be used to make profitable trading strategies. Company names can be recognized and simple templates describing company actions can be automatically filled using parsing or pattern matching on words in or near the sentence containing the company name. These templates can be clustered into groups which are statistically correlated with changes in the stock prices. The system is composed of two parts: message understanding component that automatically fills in simple templates and a statistical correlation component that tests the correlation of these patterns to increases or decreases in the stock price. The methods can be applied to a broad range of text, including articles in online newspapers such as the Wall Street Journal, financial newsletters, radio &TV transcripts and annual reports. In an enhanced embodiment of the system statistical patterns in Internet usage data and Internet data such as newly released textual information on Web pages are further leveraged.

US Patent:

20030005074, Jan 2, 2003

Filed:

Apr 25, 2001

Appl. No.:

09/842477

Inventors:

Frederick Herz - Warrington PA, US
Jonathan Smith - Princeton NJ, US
Paul Labys - Logan UT, US
Jason Eisner - Baltimore MD, US

International Classification:

G06F015/167
H04L012/26

US Classification:

709/216000, 370/229000

Abstract:

A communications method utilizes memory areas to buffer portions of the media streams. These buffer areas are shared by user applications, with the desirable consequence of reducing workload for the server system distributing media to the user (client) applications. The preferred method allows optimal balancing of buffering delays and server loads, as well as optimal choice of buffer contents for the shared memory buffers.

US Patent:

20090254971, Oct 8, 2009

Filed:

Apr 3, 2009

Appl. No.:

12/417747

Inventors:

Frederick S. M. Herz - Warrington PA, US
Walter Paul Labys - Salt Lake City UT, US
David C. Parkes - Philadelphia PA, US
Sampath Kannan - Philadelphia PA, US
Jason M. Eisner - Baltimore MD, US

Assignee:

Pinpoint, Incorporated - Fort Worth TX

International Classification:

G06F 17/00
G06Q 10/00

US Classification:

726 1, 705 1, 726 26

Abstract:

A secure data interchange system enables information about bilateral and multilateral interactions between multiple persistent parties to be exchanged and leveraged within an environment that uses a combination of techniques to control access to information, release of information, and matching of information back to parties. Access to data records can be controlled using an associated price rule. A data owner can specify a price for different types and amounts of information access.

US Patent:

20130030981, Jan 31, 2013

Filed:

Oct 5, 2012

Appl. No.:

13/646449

Inventors:

Frederick S.M. Herz - Milton WV, US
Lyle H. Ungar - Philadelphia PA, US
Jason M. Eisner - Baltimore MD, US
Walter Paul Labys - Fairfax VA, US

International Classification:

G06Q 40/04

US Classification:

705 37

Abstract:

A method of using natural language processing (NLP) techniques to extract information from online news feeds and then using the information so extracted to predict changes in stock prices or volatilities. These predictions can be used to make profitable trading strategies. Company names can be recognized and simple templates describing company actions can be automatically filled using parsing or pattern matching on words in or near the sentence containing the company name. These templates can be clustered into groups which are statistically correlated with changes in the stock prices. The system is composed of two parts: message understanding component that automatically fills in simple templates and a statistical correlation component that tests the correlation of these patterns to increases or decreases in the stock price. The methods can be applied to a broad range of text, including articles in online newspapers such as the Wall Street Journal, financial newsletters, radio & TV transcripts and annual reports. In an enhanced embodiment of the system statistical patterns in Internet usage data and Internet data such as newly released textual information on Web pages are further leveraged.

US Patent:

20130097664, Apr 18, 2013

Filed:

Dec 3, 2012

Appl. No.:

13/692151

Inventors:

Walter Paul Labys - Salt Lake City UT, US
David C. Parkes - Philadelphia PA, US
Sampath Kannan - Philadelphia PA, US
Jason M. Eisner - Baltimore MD, US

Assignee:

Pinpoint, Incorporated - Chicago IL

International Classification:

H04L 29/06

US Classification:

726 1

Abstract:

A secure data interchange system enables information about bilateral and multilateral interactions between multiple persistent parties to be exchanged and leveraged within an environment that uses a combination of techniques to control access to information, release of information, and matching of information back to parties. Access to data records can be controlled using an associated price rule. A data owner can specify a price for different types and amounts of information access.

US Patent:

20220327288, Oct 13, 2022

Filed:

Apr 13, 2021

Appl. No.:

17/229637

Inventors:

- Redmond WA, US
Adam D. PAULS - San Francisco CA, US
Daniel Louis KLEIN - Orinda CA, US
Eui Chul SHIN - San Francisco CA, US
Christopher H. LIN - Bellevue WA, US
Pengyu CHEN - Union City CA, US
Subhro ROY - Walnut Creek CA, US
Jason Michael EISNER - Baltimore MD, US
Benjamin Lev SNYDER - Bellevue WA, US
Samuel McIntire THOMSON - Berkeley CA, US

Assignee:

Microsoft Technology Licensing, LLC - Redmond WA

International Classification:

G06F 40/30
G06F 40/55
G06F 40/58
G06F 40/205

Abstract:

Systems and methods are provided for automatically generating a program based on a natural language utterance using semantic parsing. The semantic parsing includes translating a natural language utterance into instructions in a logical form for execution. The methods use a pre-trained natural language model and generate a canonical utterance as an intermediate form before generating the logical form. The natural language model may be an auto-regressive natural language model with a transformer to paraphrase a sequence of words or tokens in the natural language utterance. The methods generate a prompt including exemplar input/output pairs as a few-shot learning technique for the natural language model to predict words or tokens. The methods further use constrained decoding to determine a canonical utterance, iteratively selecting sequence of words as predicted by the model against rules for canonical utterances. The methods generate a program based on the canonical utterance for execution in an application.

US Patent:

20230130409, Apr 27, 2023

Filed:

Jul 6, 2022

Appl. No.:

17/811060

Inventors:

- Milton WV, US
Lyle H. Ungar - Philadelphia PA, US
Jason M. Eisner - Baltimore MD, US
Walter Paul Labys - Fairfax VA, US

International Classification:

G06Q 40/06
G06Q 40/04

Abstract:

A method of using natural language processing (NLP) techniques to extract information from online news feeds and then using the information so extracted to predict changes in stock prices or volatilities. These predictions can be used to make profitable trading strategies. Company names can be recognized and simple templates describing company actions can be automatically filled using parsing or pattern matching on words in or near the sentence containing the company name. These templates can be clustered into groups which are statistically correlated with changes in the stock prices. The system is composed of two parts: message understanding component that automatically fills in simple templates and a statistical correlation component that tests the correlation of these patterns to increases or decreases in the stock price. The methods can be applied to a broad range of text, including articles in online newspapers such as the Wall Street Journal, financial newsletters, radio &TV transcripts and annual reports. In an enhanced embodiment of the system statistical patterns in Internet usage data and Internet data such as newly released textual information on Web pages are further leveraged.