Patent Abstract:
To facilitate legal research, companies, such as Thomson West provide subscription-based online information-retrieval systems. Seeking to improve these and/or related systems, the present inventors devised, among other things, an exemplary legal research system that performs a conventional search to identify a set of starter documents and then leverages the metadata associated with these starter documents to identify another larger set of relevant documents. Documents in this alternate set are then scored using, for example, a learning machine and feature vectors that account for metadata relationships between the starter documents and alternate documents.

Full Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application claims priority to U.S. provisional application 60/723,322 filed on Oct. 4, 2005. The provisional application 60/723,322 is incorporated herein by reference in its entirety. This application claims the benefit of priority as a continuation in part to U.S. patent application Ser. No. 11/028,476, filed on Jan. 3, 2005 entitled SYSTEMS, METHODS, INTERFACES AND SOFTWARE FOR EXTENDING SEARCH RESULTS BEYOND INTITIAL QUERY-DEFINED BOUNDARIES, which in turn claims priority to U.S. provisional application 60/533,819 filed Dec. 31, 2003. 
    
    
     COPYRIGHT NOTICE AND PERMISSION 
     A portion of this patent document contains material subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all copyrights whatsoever. The following notice applies to this document: Copyright © 2005, West Services Inc. 
     TECHNICAL FIELD 
     Various embodiments of the present invention concern information-retrieval systems, such as those that provide legal documents or other related content. 
     BACKGROUND 
     The American legal system, as well as some other legal systems around the world, relies heavily on written judicial opinions, the written pronouncements of judges, to articulate or interpret the laws governing resolution of disputes. Each judicial opinion is not only important to resolving a particular legal dispute, but also to resolving similar disputes, or cases, in the future. Because of this, judges and lawyers within our legal system are continually researching an ever-expanding body of past opinions, or case law, for the ones most relevant to resolution of disputes. 
     To facilitate these searches West Publishing Company of St. Paul, Minn. (doing business as Thomson West) collects judicial opinions from courts across the United States, and makes them available electronically through its Westlaw™ legal research system. Users access the judicial opinions, for example, by submitting keyword queries for execution against a jurisdictional database of judicial opinions or case law. The Westlaw system also includes a ResultsPlus feature which suggest other content, particularly secondary legal content, such as legal encyclopedia articles, that are relevant to the specific case law queries. (See for example, US20050228788A1, which is incorporated herein by reference.) 
     At least one problem the present inventors recognized with this effective and highly successful system is that it does not fully appreciate the “one good case” methodology that many, if not most, legal researchers uses when conducting their research. This method generally entails a user running a relatively broad or intermediate query, manually identifying one highly relevant case law document from the search results, and then leveraging that good document to find other relevant documents. 
     Accordingly, the present inventors have recognized a need for improvement of information-retrieval systems for legal documents and potentially other document retrieval systems. 
     SUMMARY 
     To address this and/or other needs, the present inventors devised, among other things, systems, methods, and software that facilitate the retrieval of highly relevant legal documents in response to queries for legal opinions (case law documents). One exemplary system receives a user query for legal opinions and runs the query against a legal opinion database and on or more other non-legal opinion databases, such as a metadata store. The metadata includes legal classification codes, associated legal head notes, and related secondary legal documents, such as legal treatises, legal encyclopedias. Metadata based on these results is then used to identify a set of key classification codes and these in turn are used to identify highly relevant case law documents. These case law document can then be used to identify other relevant case law and/or non-case law documents based on citation relationships, text similarities, and so forth. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a diagram of an exemplary information-retrieval system  100  corresponding to one or more embodiments of the invention; 
         FIG. 2  is a flowchart corresponding to one or more exemplary methods of operating system  100  and one or more embodiments of the invention; and 
         FIG. 3  is a diagram of an exemplary user interface  300  corresponding to one or more embodiments of the invention. 
     
    
    
     DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS 
     This description, which references and incorporates the above-identified Figures, describes one or more specific embodiments of an invention. These embodiments, offered not to limit but only to exemplify and teach the invention, are shown and described in sufficient detail to enable those skilled in the art to implement or practice the invention. Thus, where appropriate to avoid obscuring the invention, the description may omit certain information known to those of skill in the art. 
     Additionally, this document incorporates by reference U.S. Provisional Patent Application 60/436,191, which was filed on Dec. 23, 2002; U.S. patent application Ser. No. 10/027,914, which was filed on Dec. 21, 2001; U.S. Provisional Patent Application 60/437,169, which was filed on Dec. 30, 2002; and U.S. Provisional Patent Application 60/480,476, which was filed on Jun. 19, 2003. One or more embodiments of the present application may be combined or otherwise augmented by teachings in the referenced applications to yield other embodiments. 
     Exemplary Information-Retrieval System 
       FIG. 1  shows an exemplary online information-retrieval (or legal research) system  100 . System  100  includes one or more databases  110 , one or more servers  120 , and one or more access devices  130 . 
     Databases  110  includes a set of primary databases  112 , a set of secondary databases  114 , and a set of metadata databases  116 . Primary databases  112 , in the exemplary embodiment, include a caselaw database  1121  and a statutes databases  1122 , which respectively include judicial opinions and statutes from one or more local, state, federal, and/or international jurisdictions. Secondary databases  114 , which contain legal documents of secondary legal authority or more generally authorities subordinate to those offered by judicial or legislative authority in the primary database, includes an ALR (American Law Reports) database,  1141 , an AMJUR database  1142 , a West Key Number (KNUM) Classification database  1143 , and an law review (LREV) database  1144 . Metadata databases  116  includes case law and statutory citation relationships, KeyCite data (depth of treatment data, quotation data, headnote assignment data, and ResultsPlus secondary source recommendation data. Also, in some embodiments, primary and secondary connote the order of presentation of search results and not necessarily the authority or credibility of the search results. 
     Databases  110 , which take the exemplary form of one or more electronic, magnetic, or optical data-storage devices, include or are otherwise associated with respective indices (not shown). Each of the indices includes terms and phrases in association with corresponding document addresses, identifiers, and other conventional information. Databases  110  are coupled or couplable via a wireless or wireline communications network, such as a local-, wide-, private-, or virtual-private network, to server  120 . 
     Server  120 , which is generally representative of one or more servers for serving data in the form of webpages or other markup language forms with associated applets, ActiveX controls, remote-invocation objects, or other related software and data structures to service clients of various “thicknesses.” More particularly, server  120  includes a processor module  121 , a memory module  122 , a subscriber database  123 , a primary search module  124 , metadata research module  125 , and a user-interface module  126 . 
     Processor module  121  includes one or more local or distributed processors, controllers, or virtual machines. In the exemplary embodiment, processor module  121  assumes any convenient or desirable form. 
     Memory module  122 , which takes the exemplary form of one or more electronic, magnetic, or optical data-storage devices, stores subscriber database  123 , primary search module  124 , secondary search module  125 , and user-interface module  126 . 
     Subscriber database  123  includes subscriber-related data for controlling, administering, and managing pay-as-you-go or subscription-based access of databases  110 . In the exemplary embodiment, subscriber database  123  includes one or more preference data structures. 
     Primary search module  124  includes one or more search engines and related user-interface components, for receiving and processing user queries against one or more of databases  110 . In the exemplary embodiment, one or more search engines associated with search module  124  provide Boolean, tf-idf, natural-language search capabilities. 
     Metadata research module  125  includes one or more search engines for receiving and processing queries against metdata databases  116  and aggregating, scoring, and filtering, recommending, and presenting results. In the exemplary embodiment, module  125  includes one or more feature vector builders and learning machines to implement the functionality described herein. Some embodiments charge a separate or additional fee for accessing documents from the second database. 
     User-interface module  126  includes machine readable and/or executable instruction sets for wholly or partly defining web-based user interfaces, such as search interface  1261  and results interface  1262 , over a wireless or wireline communications network on one or more accesses devices, such as access device  130 . 
     Access device  130  is generally representative of one or more access devices. In the exemplary embodiment, access device  130  takes the form of a personal computer, workstation, personal digital assistant, mobile telephone, or any other device capable of providing an effective user interface with a server or database. Specifically, access device  130  includes a processor module  131  one or more processors (or processing circuits)  131 , a memory  132 , a display  133 , a keyboard  134 , and a graphical pointer or selector  135 . 
     Processor module  131  includes one or more processors, processing circuits, or controllers. In the exemplary embodiment, processor module  131  takes any convenient or desirable form. Coupled to processor module  131  is memory  132 . 
     Memory  132  stores code (machine-readable or executable instructions) for an operating system  136 , a browser  137 , and a graphical user interface (GUI)  138 . In the exemplary embodiment, operating system  136  takes the form of a version of the Microsoft Windows operating system, and browser  137  takes the form of a version of Microsoft Internet Explorer. Operating system  136  and browser  137  not only receive inputs from keyboard  134  and selector  135 , but also support rendering of GUI  138  on display  133 . Upon rendering, GUI  138  presents data in association with one or more interactive control features (or user-interface elements). (The exemplary embodiment defines one or more portions of interface  138  using applets or other programmatic objects or structures from server  120 .) 
     More specifically, graphical user interface  138  defines or provides one or more display regions, such as a query or search region  1381  and a search-results region  1382 . Query region  1381  is defined in memory and upon rendering includes one or more interactive control features (elements or widgets), such as a query input region  1381 A, a query submission button  1381 B. Search-results region  1382  is also defined in memory and upon rendering presents a variety of types of information in response to a case law query submitted in region  1381 . In the exemplary embodiment, the results region identifies one or more source case law documents (that is, one ore good cases, usually no more than five), jurisdictional information, issues information, additional key cases, key statutes, key briefs or trial documents, key analytical materials, and/or additional related materials. (See  FIG. 3 , which is described below, for a more specific example of a results region.) Each identified document in region  1382  is associated with one or more interactive control features, such as hyperlinks, not shown here. User selection of one or more of these control features results in retrieval and display of at least a portion of the corresponding document within a region of interface  138  (not shown in this figure.) Although  FIG. 1  shows query region  1381  and results region  1382  as being simultaneously displayed, some embodiments present them at separate times. 
     Exemplary Operation 
       FIG. 2  shows a flow chart  200  of one or more exemplary methods of operating a system, such as system  100 . Flow chart  200  includes blocks  210 - 250 , which, like other blocks in this description, are arranged and described in a serial sequence in the exemplary embodiment. However, some embodiments execute two or more blocks in parallel using multiple processors or processor-like devices or a single processor organized as two or more virtual machines or sub processors. Some embodiments also alter the process sequence or provide different functional partitions to achieve analogous results. For example, some embodiments may alter the client-server allocation of functions, such that functions shown and described on the server side are implemented in whole or in part on the client side, and vice versa. Moreover, still other embodiments implement the blocks as two or more interconnected hardware modules with related control and data signals communicated between and through the modules. Thus, the exemplary process flow (in  FIG. 2  and elsewhere in this description) applies to software, hardware, and firmware implementations. 
     Block  210  entails presenting a search interface to a user. In the exemplary embodiment, this entails a user directing a browser in an client access device to internet-protocol (IP) address for an online information-retrieval system, such as the Westlaw system and then logging onto the system. Successful login results in a web-based search interface, such as interface  138  in  FIG. 1  being output from server  120 , stored in memory  132 , and displayed by client access device  130 . 
     Using interface  138 , the user can define or submit a case law query and cause it to be output to a server, such as server  120 . In other embodiments, a query may have been defined or selected by a user to automatically execute on a scheduled or event-driven basis. In these cases, the query may already reside in memory of a server for the information-retrieval system, and thus need not be communicated to the server repeatedly. Execution then advances to block  220 . 
     Block  220  entails receipt of a query. In the exemplary embodiment, the query includes a query string and/or a set of target databases (such as jurisdictional and/or subject matter restricted databases), which includes one or more of the select databases. In some embodiments, the query string includes a set of terms and/or connectors, and in other embodiment includes a natural-language string. Also, in some embodiments, the set of target databases is defined automatically or by default based on the form of the system or search interface. Also in some embodiments, the received query may include temporal restrictions defining whether to search secondary resources. In any case, execution continues at block  230 . 
     Block  230  entails identifying a starter set of documents based on the received query. In the exemplary embodiment, this entails the server or components under server control or command, executing the query against the primary databases and identifying documents, such as case law documents, that satisfy the query criteria. A number of the starter set of documents, for example 2-5, based on relevance to the query are then selected as starter cases. Execution continues at block  240 . 
     Block  240  entails identifying a larger set of recommended cases (documents) based on the starter set of cases. In the exemplary embodiment, this entails searching the metadata databases based on the citations in and to the starter cases, based on secondary legal documents that are associated with the starter cases, legal classes (West KeyNumber classifications) associated with the starter cases, and statutes query to obtain a set of relevant legal classes. In the exemplary embodiment, this larger set of recommended cases, which is identified using metadata research module  126 , may include thousands of cases. In some embodiments, the set of recommended cases is based only on metadata associated with the set of starter cases (documents.) 
     Block  250  entails ranking the recommended cases. In the exemplary embodiment, this ranking entails defining a feature vector for each of the recommended cases (documents) and using a support vector machine (or more generally a learning machine) to determine a score for each of the documents. The support vector machine may include a linear or nonlinear kernel. Exemplary features for feature vectors include: 
     NumObservations—how many ways to get from source to recommendation 
     NumSources—how many sources (starter documents) connect to recommendation 
     NumReasons—how many kinds of paths to recommendation 
     MaxQuotations—Maximum of numQuotations value in citations 
     TFIDFScore—Based on text similarity of text (as used by ResultsPlus (RPD)) 
     RPWeightedScore—Based on number of RPD recommendations shared and their scores 
     NumSharedRPDocs—Same as RPWeightedScore, but not based on score 
     KNWeightedScore—Based on the number of key numbers (legal classification codes) shared and their importance 
     NumSharedKeyNumbers—same thing but not based on score 
     NumSourcesCiting—Number of sources that directly cite a recommendation 
     NumCitedSources—Number of sources cited by a recommendation 
     NumCoCitedCases—Number of cases with co-citation between a source and a recommendation 
     NumCoCitedByCases—Number of cases with bibilographic coupling between source and recommended documents 
     NumSharedStatutes—Number of statutes in common 
     SimpleKeyciteCiteCount—Raw Number of times recommended case was cited by any case 
     Some embodiments use all these features, whereas others use various subsets of the features. Execution proceeds to block  260 . 
     Block  260  entails presenting search results. In the exemplary embodiment, this entails displaying a listing of one or more of the top ranked recommended case law documents in results region, such as region  1382  in  FIG. 1 . In some embodiments, the results may also include one or more non-case law documents that share a metadata relationship with the top-ranked recommended case law documents; legal classification identifiers may also be presented.  FIG. 3  shows a detailed example of this type of results presentation. Other embodiments may present a more limited result set including identifiers for the top ranked documents and a set of legal classification codes. 
     CONCLUSION 
     The embodiments described above are intended only to illustrate and teach one or more ways of practicing or implementing the present invention, not to restrict its breadth or scope. The actual scope of the invention, which embraces all ways of practicing or implementing the teachings of the invention, is defined only by the following claims and their equivalents.

Technology Classification (CPC): 6