Buchalter Nemer 1000 Wilshire Boulevard Suite 1500, Los Angeles, CA 90017 2138915067 (Office)
Licenses:
California - Active 1998
Experience:
Shareholder at Buchalter Nemer - 2013-present Adjunct Professor at Pepperdine University School of Law - 2007-present Partner at Kirkland & Ellis - 1998-2013
Education:
Pepperdine University School Of Law Degree - JD - Juris Doctor - Law Graduated - 1998 Dickinson College Degree - BA - Bachelor of Arts Graduated - 1995
Specialties:
Litigation - 50% Arbitration - 25% Appeals - 25%
Languages:
English
Associations:
Los Angeles County Bar Foundation - Director, 2007-present Western Center on Law & Poverty - Director, 2007-present Los Angeles County Bar Association, 1998-present California State Bar Committee on Federal Courts - Member, 2005-2007 Western Center on Law & Poverty - Advisory Board President, 2004-2007
Us Patents
Adaptive User Interface For Real-Time Search Relevance Feedback
A method and apparatus for dynamically adjusting the user interface of a search engine in order to effectively communicate the improved relevancy achieved through real-time implicit re-ranking of search results is described. Real-time implicit re-ranking occurs without delay after every user action as the search is being conducted, so finding methods of immediately altering the search page without disrupting the user experience is important. Graphical icons next to search results are employed to enable generating and removing re-ranked results, referred to as “recommended” search results. Clusters based on the real-time user model are also displayed to facilitate query reformulations. Sponsored links are selected using the real-time user model along with a combination of RPC and CTR information and are displayed in a manner similar to the organic results, or used to replace the initial sponsored links altogether.
Real Time Implicit User Modeling For Personalized Search
Mark Cramer - San Francisco CA, US ChengXiang Zhai - Champaign IL, US Xuehua Shen - Urbana IL, US Bin Tan - Champaign IL, US
Assignee:
Surf Canyon, Inc. - Oakland CA The Board of Trustees of The University of Illinois - Urbana IL
International Classification:
G06F 7/00 G06F 17/00
US Classification:
707723, 707753
Abstract:
A method and apparatus for utilizing user behavior to immediately modify sets of search results so that the most relevant documents are moved to the top. In one embodiment of the invention, behavior data, which can come from virtually any activity, is used to infer the user's intent. The updated inferred implicit user model is then exploited immediately by re-ranking the set of matched documents to best reflect the information need of the user. The system updates the user model and immediately re-ranks documents at every opportunity in order to constantly provide the most optimal results. In another embodiment, the system determines, based on the similarity of results sets, if the current query belongs in the same information session as one or more previous queries. If so, the current query is expanded with additional keywords in order to improve the targeting of the results.
Adaptive User Interface For Real-Time Search Relevance Feedback
A method and apparatus for dynamically adjusting the user interface of a search engine in order to effectively communicate the improved relevancy achieved through real-time implicit re-ranking of search results is described. Real-time implicit re-ranking occurs without delay after every user action as the search is being conducted, so finding methods of immediately altering the search page without disrupting the user experience is important. Graphical icons next to search results are employed to enable generating and removing re-ranked results, referred to as “recommended” search results. Clusters based on the real-time user model are also displayed to facilitate query reformulations. Sponsored links are selected using the real-time user model along with a combination of RPC and CTR information and are displayed in a manner similar to the organic results, or used to replace the initial sponsored links altogether.
Dynamic Search Engine Results Employing User Behavior
A method and apparatus for dynamically modifying search results “on the fly” based on the behavior of the user currently conducting a search. In one embodiment, data regarding user behavior is gathered from virtually any activity, including clicks on links, dwell times, downloads, transactions and cursor movements. Subordinate keywords are generated to reflect the intent of the user as inferred from the user's behavior. Subordinate keywords, as opposed to traditional primary keywords, are keywords that are identified as important to the search, but are not necessarily essential for a matched document. They are automatically generated by the system from a variety of places, such as documents clicked on by the user as well as documents that are skipped. The system uses the subordinate keywords to dynamically re-rank matched documents and advertisements to best reflect the inferred intent of the user in order to continuously provide the most relevant results.
Dynamic Search Engine Results Employing User Behavior
A method and apparatus for dynamically modifying search results “on the fly” based on the behavior of the user currently conducting a search. In one embodiment, data regarding user behavior is gathered from virtually any activity, including clicks on links, dwell times, downloads, transactions and cursor movements. Subordinate keywords are generated to reflect the intent of the user as inferred from the user's behavior. Subordinate keywords, as opposed to traditional primary keywords, are keywords that are identified as important to the search, but are not necessarily essential for a matched document. They are automatically generated by the system from a variety of places, such as documents clicked on by the user as well as documents that are skipped. The system uses the subordinate keywords to dynamically re-rank thatched documents and advertisements to best reflect the inferred intent of the user in order to continuously provide the most relevant results.
Dynamic Search Engine Results Employing User Behavior
A method and apparatus for dynamically modifying search results “on the fly” based on the behavior of the user currently conducting a search. In one embodiment, data regarding user behavior is gathered from virtually any activity, including clicks on links, dwell times, downloads, transactions and cursor movements. Subordinate keywords are generated to reflect the intent of the user as inferred from the user's behavior. Subordinate keywords, as opposed to traditional primary keywords, are keywords that are identified as important to the search, but are not necessarily essential for a matched document. They are automatically generated by the system from a variety of places, such as documents clicked on by the user as well as documents that are skipped. The system uses the subordinate keywords to dynamically re-rank matched documents and advertisements to best reflect the inferred intent of the user in order to continuously provide the most relevant results.
Adaptive User Interface For Real-Time Search Relevance Feedback
A method and apparatus for dynamically adjusting the user interface of a search engine in order to effectively communicate the improved relevancy achieved through real-time implicit re-ranking of search results is described. Real-time implicit re-ranking occurs without delay after every user action as the search is being conducted, so finding methods of immediately altering the search page without disrupting the user experience is important. Graphical icons next to search results are employed to enable generating and removing re-ranked results, referred to as “recommended” search results. Clusters based on the real-time user model are also displayed to facilitate query reformulations. Sponsored links are selected using the real-time user model along with a combination of RPC and CTR information and are displayed in a manner similar to the organic results, or used to replace the initial sponsored links altogether.
Adaptive User Interface For Real-Time Search Relevance Feedback
- San Francisco CA, US Mark D. Cramer - San Francisco CA, US
International Classification:
G06F 17/30 H04L 29/08 G06Q 30/02
Abstract:
A method and apparatus for dynamically adjusting the user interface of a search engine in order to effectively communicate the improved relevancy achieved through real-time implicit re-ranking of search results is described. Real-time implicit re-ranking occurs without delay after every user action as the search is being conducted, so finding methods of immediately altering the search page without disrupting the user experience is important. Graphical icons next to search results are employed to enable generating and removing re-ranked results, referred to as “recommended” search results. Clusters based on the real-time user model are also displayed to facilitate query reformulations. Sponsored links are selected using the real-time user model along with a combination of RPC and CTR information and are displayed in a manner similar to the organic results, or used to replace the initial sponsored links altogether.
Lee Hartog, Linda Lafrentz, Gerrie Peterson, Paula Shabino, Peg Steffen, Deb Kohnen, Leslee Trottman, Nancy Warner, Karen Kinney, Debra Stone, Debby Hall
Mark Cramer (1969-1973), Marilyn Deroiun (1966-1970), steve waller (1963-1967), Juanita Scott (1988-1992), Tom Traubert (1976-1980), muriel DuBois (1962-1966)
Googleplus
Mark Cramer
Work:
Surf Canyon - CEO (2006)
Education:
Massachusetts Institute of Technology - EE, Harvard Business School
Tagline:
Entrepreneur and Inventor
Mark Cramer
Work:
MMM Productions - Head of Production Spatial Harmonics Group - Production Manager (2006)
Education:
Emerson College - BA Theatre Studies: Acting and Directing