Wendong Dong Zhu

US Patent:

20090132385, May 21, 2009

Filed:

Nov 19, 2008

Appl. No.:

12/273558

Inventors:

Riku Inoue - Stanford CA, US
Wendong Zhu - Berwyn PA, US

Assignee:

Techtain Inc. - Palo Alto CA

International Classification:

G06Q 30/00

US Classification:

705 26

Abstract:

According to a computer implemented method and system for matching user-generated text content, users “freely” specify content by means of fed-in texts which are matched automatically, according to rules in the embodiment. An embodiment of the invention allows customers to specify what items or services to request or offer by adding, to the “MyHaves” or “MyWants” selection criteria, using typed-in descriptions. Traditionally, for the purpose of matching supplies and demands, the specification of an individual's “wants” and “haves” is done by selecting options that are predefined by, or hard-coded into, the system's “drop-down menu”—rather than allowing customers to freely define what they want or have. This method under consideration, however, provides an efficacious solution: customers are free to request an item or service by entering standard descriptive texts describing what s/he wants in a customizable manner very akin to the flexibility associated with verbal speech, with the assurance that these human-entered texts will be matched automatically. Similarly, a customer is free to offer an item or service in the aforementioned (text-descriptive) way. The entered texts are in the form of a specific human language (e.g. English, Chinese, etcetera) using the desired input device, such as a computer keyboard. The system algorithm of an implementation then “crawls” through the network of user generated texts (user-defined texts) to find matches between what people are offering and what others are requesting, while watching out for typographical errors (in the text content) made by customers. That is to say, the algorithm in the embodiment scours the texts in the “MyWants” section of requesters and sees if there are corresponding matches found in the “MyHaves” section of offerers, while paying attention to certain system rules.Although the invention essentially lies in the ability to match raw user-generated texts—that fall out of system-provided categories—to achieve any desired purpose of an embodiment, the invention has applicability in sundry areas where utility may be derived. In an embodiment of the invention, for example, when a match is found, the system automatically triggers an email that is sent to the offerer, notifying him/her that a fellow customer wants what the offerer-customer has to offer. If the offerer-customer agrees to deliver the item or service to the requester, the implementation proceeds to require the requester customer to confirm receipt once the item is received. The utility here is the expeditious re-allocation of resources whose descriptions fall outside the predefined categories of the system and, consequently, may only be accurately provided by the persons wanting or offering the resources (items or services).

US Patent:

20090094116, Apr 9, 2009

Filed:

Oct 6, 2008

Appl. No.:

12/245770

Inventors:

Oladayo Olagunju - Palo Alto CA, US
Wendong Zhu - Berwyn PA, US

Assignee:

Techtain Inc. - Palo Alto CA

International Classification:

G06Q 30/00

US Classification:

705 14, 705 1

Abstract:

According to a computer implemented approach for expeditious resource re-allocation in a network, customers specify what items or services to request or offer by adding to the “MyHaves” or “MyWants” selection criteria. According to the method, a customer requests an item or service by adding it to his/her “MyWants” in any of the following three ways: using a single click, searching and then adding, or feeding in user-defined-inputs. Similarly, a customer declares to offer an item or service by adding it to his/her “MyHaves” in any of the three aforementioned ways. The system algorithm of an embodiment “crawls” to find matches between the “MyHaves” of offerers and the “MyWants” of requesters, paying attention to and giving priority to the proximity and social network rules in the system. When a match is found, the system automatically triggers an email that is sent to the offerer, notifying him/her that a fellow customer wants what the offerer-customer has. If the offerer-customer agrees to deliver the item or service to the requester, the implementation proceeds to require the requester customer to confirm receipt once the item is received. Confirmation of receipt by a requester causes the system to award points or credits to the offerer as a form of reward. These points can then be used—by the awarded offerer—to enjoy discounted purchases at selected system partner businesses. The point system may be implemented adopting a variety of methodologies. In an embodiment of the present invention, customers (users) communicate with one another using the system's “messenger tool” called “TtMessage”, and control the re-allocation of resources by forming their own circles using the “TtCircle” capability therein.

US Patent:

20220277355, Sep 1, 2022

Filed:

Jan 4, 2022

Appl. No.:

17/568522

Inventors:

- San Francisco CA, US
Jin Huang - San Francisco CA, US
Marc Cohen - San Francisco CA, US
Wendong Zhu - San Francisco CA, US

International Classification:

G06Q 30/02

Abstract:

A health care provider (HCP) engagement engine is disclosed. The HCP engagement engine facilitates effective communication between pharmaceutical sales representatives (medical reps) and HCPs by generating, using machine learning algorithms, messages for the medical reps to send to HCPs. The recommended messages may be sent over a network and may include email messages, text messages, or online chat messages. The recommended messages may be drafted entirely by the engagement engine or may be drafted as addenda to messages already used by the medical reps. The HCP engagement engine uses historical data on actions performed by the HCPs and medical reps, as well as data collected from historical message recommendation events, in order to produce message recommendations.