This application claims the benefit under 35 U.S.C. 119(e) of U.S. Provisional Patent Application Ser. No. 61/107,930 filed Oct. 23, 2008, which is incorporated herein by reference in its entirety and made a part hereof.
This application is related to U.S. patent application Ser. No. 11/494,278, entitled “Patent Mapping,” by Steven W. Lundberg, Janal M. Kalis, and Pradeep Sinha, filed Jul. 27, 2006, which is incorporated herein by reference; and is further related to U.S. patent application Ser. No. 11/888,632, entitled “Patent Tracking,” by Steven W. Lundberg and Janal M. Kalis, filed Aug. 1, 2007 which is incorporated herein by reference; and is further related to U.S. patent application Ser. No. 10/710,656, entitled “Patent Mapping,” by Steven W. Lundberg, Janal M. Kalis, and Pradeep Sinha, filed Jul. 27, 2004 which is incorporated herein by reference and corresponding PCT application PCT/US2005/026768 filed Jul. 27, 2005.
Tools for identifying patents for a particular purpose such as a prior art search, validity analysis, or a freedom to operate investigation, operate by performing Boolean queries using various search operators. These operators allow for searching by date, terms, document number, and patent classification, among others. These tools further allow for searching individual document portions such as a document title, abstract, or claim set.
Other searching tools accept freeform text. Such tools accept a freeform text block and extract information from the text block deemed most likely to return acceptable results. However, such tools are still limited to only performing Boolean queries and displaying a list of results.
BRIEF DESCRIPTION OF THE DRAWINGS
These search tools often provide large numbers of results, most of which are irrelevant. These tools fail to present results in a manner allowing for quick relevancy determinations. The presentation also fails to provide enough detail suggesting how to adjust a search for obtaining only relevant results. Further, the search tools provide the documents of the result set in a manner very similar to the traditional paper format of the documents.
Some example embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings in which:
FIG. 1 is a diagram of a system, according to an example embodiment.
FIG. 2 is a block diagram of a server device, according to an example embodiment.
FIGS. 3-8 are data model diagrams, according to example embodiments.
FIGS. 9-15 are user interfaces, according to example embodiments.
FIGS. 16-22 are example generated charts, according to example embodiments.
FIG. 23 is a computer system, according to an example embodiment.
The following detailed description of the present subject matter refers to the accompanying drawings which show, by way of illustration, specific aspects and embodiments in which the present subject matter may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the present subject matter. Other embodiments may be utilized and structural, logical, and electrical changes may be made without departing from the scope of the present subject matter. References to “an”, “one”, or “various” embodiments in this disclosure are not necessarily to the same embodiment, and such references contemplate more than one embodiment. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope is defined only by the appended claims, along with the full scope of legal equivalents to which such claims are entitled.
The subject matter herein provides systems, software, methods, and data structures for patent mapping, ranking and rating of patents, searching, and generating visual representations of the patents and patent portfolios to quickly analyze the patents for many reasons including, but not limited to, claim coverage and value. In an example embodiment, a patent portfolio may comprise one or more patents that may or may not be commonly owned or related. The collection of patent portfolios and patents may be stored in one or more databases. A patent may belong to more than one portfolio at the same time. In an example embodiment, the underlying patents and patent claims included in each patent portfolio may be categorized by patent concepts (sometimes referred herein as concepts) such as scope concepts (SC) and technology categories (TC).
In an example embodiment, technology categories are categories that claims relate to, but are not necessarily limited to. For example, a claim to a pulse generator may be put in the technology category “pacemaker”, but not be limited to a pacemaker per se—perhaps the claim merely says that the pulse generator generates a pulse of certain type that is useful for pacing, but pacing does not appear in the claim. Hence, the claim relates to the technology category “pacemaker,” but it is not limited to being a pacemaker.
In an example embodiment, scope concepts are concepts that a claim is limited to. This is contrast to technology categories, where the claim may be mapped to a TC but it not necessarily limited to it. A scope concept may defined in a way to give the concept a context that a user can understand without necessarily having to look at the corresponding claim language. For example, if the scope concept is “method or apparatus for cardiac rhythm management”, and it is mapped to claim A, then claim A by definition is limited to this application, such that if a target device does not perform cardiac rhythm management, then it would not infringe claim A.
In an example embodiment, there are two types of scope concepts: 1) high level scope concepts that are like technical categories in the sense they are broad and general and apply to many claims in a portfolio; and 2) scope concepts that are specific to a limited number of claims—for example all claims in a patent may be limited to a very specific distinguishing feature, and this feature could be the basis for a scope concept.
In some example embodiments, high level scope concepts may be defined prior to mapping, and then assigned as applicable. For example, several scope concepts like: atrial pacing, ventricular pacing, defibrillation method or device, etc, may be defined. Then a mapping team may go through all claims in a portfolio and map these scope concepts to claims that are limited to these concepts. After the mapping is complete, an analysis may be done showing how many claims in the portfolio are limited to each of these scope concepts, and the claims may be presented for each SC. This may be useful is disqualify claims that are not of interest to a particular target (e.g., if an analysis is being done to find a claim that covers an alleged infringer). In some example embodiments, specific scope concepts are mapped patent by patent or by patent family. These may enable a person to create one or two scope concepts that can be mapped across all claims in given patent, a family of patents, or across a portion of a patent portfolio. In order to effectively formulate a scope concept that may be globally useful across a patent portfolio, it may be useful to be able to examine multiple patent claims at the same time even if they are not all in the same patent or patent family.
FIG. 1 illustrates an example system to implement the methods described herein. Shown is a user 102 and a user device 104. The user device 104 may be, for example, a personal computer, mobile phone, or personal digital assistant. The user device 104 may be a computer system as described in FIG. 17. Users of the system may include specialized personnel trained to map patent claims as well as personnel trained to analyze the resulting claim map. The user device 102 may communicate with a server device 106 over a network 108 (e.g., the Internet) using a variety of communication means including, but not limited to, wired and wireless communication. The server device 106 may be a computer system as described in FIG. 17. In an example embodiment, the user 102 requests patent claims 110 from the server device 106 and transmits concept mappings 112 back to the server device 106 through the user device 104 via the network 108. In various embodiments, one or more software applications are executed on the user device which facilitate the interactions and data transmissions between user 102, user device 104, and server device 106. Other information needed to complete the methods described herein may be transmitted between the user device 102 and server device 106 according to example embodiments.
FIG. 2 illustrates an example server device 200. In an example embodiment, the server device includes one or more modules, databases, and engines. The various modules, databases, and engines may interact with each other and may take on the functionality of other modules, databases, and engines. Databases, according to an example embodiment, generally refer to sets of data stored in tables and may be implemented using a variety of database solutions including Oracle and MySQL. Engines, according to an example embodiment, generally refer to the generation of a product/image that is presented to a user (e.g., a webpage). Modules, according to an example embodiment, generally refer to functionality or features of the system that a user may invoke. For example, the mapping module may provide the necessary logic to create a mapping between a concept and a patent claim. According to an example embodiment, server device 200 includes an account database 202, a mining module 204, visualization engine 206, a web server engine 208, a ranking module 210, a patent database 212, a valuation module 214, a tracking module 216, a concept database 218, a patent claim database 220, a patent set database 222, a mapping module 224, and an ontology database 226.
In various embodiments, the modules, engines, and databases are implemented in a combination of software and hardware. For example, a mapping module can be stored as set of instructions stored on a machine-readable medium. The instructions can be executed on a processor and cause a machine to perform operations related to mapping. Additionally, the visual presentation of data in not limited to engines and may be done by modules as well. Similarly, engines may contain underlying logic dictating on how each engine functions and interacts with the user, software, and hardware of the system. In various embodiments, the modules, engines, and databases are combined.
In an example embodiment, the account database 202 includes data pertaining to the different users of the system. In some embodiments, different levels of user are defined. For example, an administrator level allows the creation of an ontology (e.g., a collection of patent concepts and keywords) and mapping of patent claims while an analysis level user may only mine the map for patent claims. The web server engine 208 may present webpages to the user via the user device. The webpages may include forms and user interfaces for the user to interact with such that the user may manipulate the underlying data stored on the server device on one or more databases.
In an example embodiment, databases 212, 218, 220, 222, and 226 store the underlying data that the server device interacts with and modifies according to user input. The patent database 212 may include information related to all the patents stored in the system such as title, filing data, assignee, etc. The concept database 218 may store all the concepts that have been defined either by the user or automatically by the system. The patent claim database 220 may include information related to patent claims including which patent they belong to as well as concepts that have been mapped to the patent claims. The patent set database 222 may store information on sets of patents that have been defined by the user. In an example embodiment, a patent set may be defined by exclusion mining (e.g., the set of patents that have NOT been mapped to a certain concept). The ontology database 226 may store information on a user defined set of concepts.
The mapping module 224, in an example embodiment, enables a user to map a concept to a patent claim. For example, the user may create and define a patent concept which is then stored in the concept database. The user may then send an indication, through the user device, that a patent claim in the patent claim database 220 should be mapped to the new concept. The indication may take the form of a type of user input such as clicking on an interface using an input device. The server device may then store this mapping in the patent claim database. For example, a relationship between the patent claim and concept may be stored in one or more of the databases.
The mining module 204, in an example embodiment, allows a user to search through the data stored in the databases to find patent claims of interest. For example, a user may wish to find all the patent claims related to a gear used in a bicycle. Rather than having the user define what the gear is, the user may indicate to the mining module what the gear is not, by indicating what concepts do not apply (exclusion mining). The mining module may search the entire universe of claims in the patent claim database, or a portion of the patent claim database, and retrieve the remaining patent claims (those claims that not have the concept) and present them to the user.
The visualization engine, in an example embodiment, generates reports and visual depictions of the data contained in a set of claims. For example, the visualization engine may generate a spreadsheet with the concepts in the concept database as rows and the patent claims as the columns. Color coding may be used to signify where a patent claim has been mapped to a concept. In some example embodiments, a user of the system may add additional data that influences the spreadsheet created. Some example embodiments include the generation of competitor landscape, freedom to operate, product coverage, validity, valuation, white space analysis, and white space claim generation spreadsheets. In various embodiments, other forms of coding are used such as shading and patterning.
The tracking module 216, according to an example embodiment, maintains information related to a specific patent, group of patents, or concept. For example, the tracking module may store information related to a patent's prosecution and litigation history such as office actions or claim amendments. Alerts (e.g., electronic mail) may be sent to a user indicating a change in a patent or patent application.
- Data Models
The ranking module 210 and valuation module 214, according to example embodiments, enable the user to provide additional information related to patents, patent claims, and concepts that may be used to determine a course of action such as abandoning a patent or pursing research in a specific field. For example, a user may indicate a specific concept as being key to her business. Further, a lawyer or other trained patent professional may provide a ranking for each patent included in her portfolio related to scope, design around protection, and detectability effort. The system may take this knowledge and through the visualization engine generate a chart that shows the highest ranked patents that also include her important concept.
In an example embodiment, data models are defined to store the information related to the patents being analyzed. FIGS. 3-8 illustrate example data models that may be utilized. These may be defined in any suitable programming language such as C, C++, Java, Ruby, etc, that allows the manipulation of data models. In some embodiments, data models are referred to as classes and both terms will be used in the following descriptions. Further, an object may refer to a specific instance of a class or data model. As one skilled in the art will recognize, there may be more than one way to define the models and the relationships between the models. The illustrated models are to be taken only as one way of implementing the systems and methods described in this application. FIGS. 3-8, in some example embodiments, provide the lower level details of the information stored in databases 212, 218, 220, 222 and 226.
FIG. 3, according to an example embodiment, illustrates data models related generally to mappable data. Shown are models and relationships for a Patent 302, Mappable Data 304, Patent Specification 306, Global Patent Ranking 308, Mapping 310, claim 312, Concept 314, Concept Type 316, Patent Inclusion 318, Patent Relation 320, Ontology Relationships 322, Ontology 324, Mapping Status 326, and Ontology Concept 328. Each model may contain one or more elements that are defined either by the system or a user. Further, as illustrated, some models are related to each in other in a one to many relationship. For example, an Ontology object 324 may be related to many Ontology Concept objects 328.
In an example embodiment, Patent model 302 includes types of information related to a patent including, but not limited to, whether or not it is an application, the number of claims, when it was filed, what organization it may belong to, the serial number, and its status. As can be seen, each piece of information may have an associated class such as a Boolean or string. In some cases, the type is actually another class (e.g, global ranking has a class of Global Ranking). Further shown are the elements of a data model that relate to another data model. For example, example Mapping Status 326, Patent Relation 320, Patent Inclusion 318, and claim 312 models all include an element of patent with a class of Patent. This relationship allows the system to examine a Claim class and determine the Patent in which the Claim is included.
In some embodiments, the Mapping 310
data model defines persistent objects that define the relationships between the a concept (e.g., technology categories and scope concept), a claim, and an ontology. As shown, there are many elements that a Mapping 320
class may include, such as, but not limited to, citations, notes, ontology, concept type and claim. Further, in an example embodiment, many Mapping objects may be related to one Ontology object and one Claim object. Thus, if one were to examine a Mapping object, there would be a relationship defining the ontology to which the object belongs to as well as the claim to which it has been assigned. In addition, there may be an integer signifying the type of concept to which the Mapping object belongs. As data model Concept Type 316
suggests each type of concept may be enumerated as well as be defined by an integer value. For example, the concept of scope concept may be given the value of ‘1.’ Also, the “object” element illustrated has an associated class of Concept 314
. Accordingly, the Mapping object may be linked to an example concept that has been defined as “two wheeled transportation.” The mapping operation element may define the relationship between the cited claim and the concept. For example, a concept may be directly mapped to a claim. Other possibilities are discussed further with reference to FIG. 10
. Accordingly, a Mapping object may contain the following information with regards to some of the displayed elements.
- claim: Claim A
- conceptType: 1
- object: Two wheeled transportation
- ontology: Bikes
- mapping operation: Directly Mapped
In an example embodiment, a Mapping object is created each time the system receives an indication a concept is to be mapped to a claim. In an embodiment, an indication may be stored that a concept is not mapped to a claim.
In an example embodiment, a Concept 314 object is created for every user defined concept as well as any concept the system may define automatically. Each Concept 314 may contain, but is not limited to elements of, conceptType, description, hidden, intelliMapAllowed, keywordLabel, name, organization, and underReview. As discussed above, a Concept 314 object may contain an enumeration of the ConceptType 316 object. For example, the conceptType element may have an example value of “scope concept.” The description element may describe when a concept should be applied to a claim or other helpful information relating to the concept. The intelliMapAllowed Boolean may indicate whether the system may automatically apply the concept to other claims included in the system. For example, a concept type might be “keyword.” These keywords may be verbatim phrases or individual words in the claim. Thus, a user may be able to safely have the system search other claims and find the same keyword and automatically create Mapping 310 objects for the keyword and found claims. The intelliMapAllowed may indicate whether the system should search automatically for these keywords.
In an example embodiment, the OntologyConcept 328 class only contains two elements, ontology and concept. An Ontology Concept 328 may be created to signify the relationship between a Concept 314 object and an Ontology 324 object. As shown, an Ontology 324 object may include many OntologyConcept objects. Also, as shown, a Concept 314 object may belong to many OntologyConcept 328 objects.
Also shown in FIG. 3, is the PatentInclusion 318 object. A PatentInclusion Object may include elements of inclusionType, patent, patentSet, ranking, reviewed, and ruleType. A PatentInclusion 318 object may be used to signify the relationship between a patent and a patentSet. This relationship is more fully explained with reference to FIG. 4.
FIG. 4, according to an example embodiment, illustrates data models related, generally, to mining mapped data. Shown are models and relationships for PatentOpinion 402, IncludedClaim 404, ScheduledIntelliMap 406, PatentSet 408, ConceptExclusion 410, PortfolioDomain 412, PatentSearch 414, PatentInclusion 416, LocalPatentRanking 418, TextInclusion 420, ConceptInclusion 422, and Concept 424 classes. In some embodiments, classes with the same name as in FIG. 3 are defined similarly. For example, Concept class 424 may contain the same elements as Concept class 314. However, as illustrated, additional functions are included that may operate on the class. For example, function “createCopy( )” is illustrated in Concept class 424.
In an example embodiment, the PatentSet 408 class operates as the central class for mining. As illustrated, many of the other classes shown relate to the PatentSet 408 class. A PatentSet object may have many PatentInclusion 416, ConceptExclusion 410, and IncludedClaim 404 objects. Also, in an example embodiment, a PatentSet object may have many ConceptInclusion 422 objects related to it by virtue of the PatentSearch 414 class. Through user interfaces presented to a user and user input, a Patent Set may be defined. This may be done by a user adding claims manually or by a more sophisticated method involving a user defining which concepts to exclude or include. The various data models support an almost endless amount of customization for users of the system in the creation of patent sets.
In an example embodiment, the created patent sets may be saved for future use, as well as themselves becoming the basis for creating a new patent set. This may enable a user to efficiently search through any number of patents. The system may operate in such a manner that when a request is made to retrieve patents included in a patent set, the system responds by applying the relationships defined by the objects for that patent set. For example, the ConceptExclusion objects. This execution method may allow newly mapped patents to be included or excluded from the patent set with no additional input from a user. Thus, if a user wishes to find the intersection between a patent set related to vehicles and a patent set related to audio, the most current mapped patents available will be presented. As will be discussed in greater detail with respect to portfolio mapping, the ability to create patent sets and combine them may greatly speed up the process of finding common concepts across patents.
FIG. 5, according to an example embodiment, illustrates data models related, generally, to annuity data. Shown are models and relationships for Patent 502, ClaimMappedUser 504, AnnuityInformation 506, PatentRanking 508, ScoringCriteria 510, and Scorer objects 512. In an example embodiment to further enable a person to quickly analyze a large group of patent claims, patents may be given a rating. In an example embodiment, only the broadest independent claim in each patent is given a ranking, as the broadest claim will often have the most value. The patent claims may be ranked according to multiple criteria, including, but not limited to scope, detectability, and the ability to design around the patent. In an example embodiment, the ranking information may be stored in a PatentRanking object and retrieved through the Scorer interface. Each criteria may be given a weighting depending on the client's needs. For example, a client may decide that scope is twice as important as the other two criteria. Therefore, the formula to rank the patents may be:
Once all of the patents have been ranked, the results may be presented to the user in a web browser, in the form of a chart, or using any other suitable display mechanism.
An AnnuityInformation object may include information related to annuities for an issued patent. Depending on the rating and annuity information of a patent, a user may automatically let patents go abandoned, a user may be alerted, or an annuity may automatically be paid. Other example embodiments will be obvious to one skilled in the art.
- Portfolio Mapping
FIG. 6, according to an example embodiment, illustrates data models related generally to patent tracking. FIG. 7, according to an example embodiment, illustrates data models related generally to products and features. FIG. 8, according to an example embodiment, illustrates data models related generally to technology hierarchies.
FIG. 9 illustrates an example user interface that may be utilized to facilitate the methods described to map patent claims, according to an example embodiment. Displayed is the title 902 of a patent portfolio, controls are also illustrated that allow a user to edit to the portfolio, list the patents in the portfolio, “quick rank,” and generate a panoramic claim map. Also shown is the “Default Ontology” 904 being used. In an example embodiment, “Quick Rank” allows a user to map all the patent claims in a patent to concepts at the same time. An ontology, in an example embodiment, includes the different concepts available to a user to map to one or more of the patent claims. Further, there is an example search criteria box 906 which allows a user to specify a search query. Included are options to narrow the search by type of claim 908 including searching independent claims, dependent claims, or both. The search expression box 910 may allow a user to specify a regular expression to use as a search query. There is also an option to have keywords highlighted 912 in the search results. In an example embodiment, this may include the searched for keywords or keywords that have previously been mapped to the claims. Also shown are options to narrow the search results by technology categories 914 and scope concepts 916.
FIG. 10 illustrates a method to map concepts to patent claims according to an example embodiment. A user interface such as the one illustrated in FIG. 9 may be used to facilitate this example method. Further, in an example embodiment, the method may be implemented using the data models and server device described above (e.g., server device 106 with reference to FIG. 1). At block 1002, a database of patent portfolios and a database of patents are maintained, each patent stored in the database of patents associated with one or more patent portfolios stored in the database of patent portfolios. A database management system may be used (DBMS) for storing and retrieving data from a data store which includes the database of patents and database of patent portfolios. In some embodiments, the DBMS is a relational database management system (RDBMS). In some other embodiments, the data store includes storing data in a Resource Description Framework Schema (RDFS). In some embodiments, communication with the data store includes using a language such as Structured Query Language (SQL) or eXtensible Markup Language (XML).
In an example embodiment, a database of ontologies may also be maintained, the ontologies including one or more patent concepts. As discussed above, an ontology may include all the metadata (patent concepts) that one may wish to map to a patent claim. For instance, the one or more patent concepts may include a technology category. The one or more patent claims may also include a scope concept, the scope concept defining a scope to which a patent claim is limited. Keywords may also be used as patent concepts. These may be any term or short phrase that appears in the claim, exactly as it appears in the claim. As these terms are taken from the claims, they may be thought of as limitations in the sense that if the term cannot be read on an accused device, the claim probably does not cover the accused device. Example user interfaces showing scope concepts in an ontology can be seen with reference to FIG. 11.
In an example embodiment, at block 1004, a search query associated with a first patent portfolio is retrieved. A user of the system may wish to search a previously created portfolio of patents. A patent portfolio may include patents that a user wishes to analyze. For example, a portfolio might include all of the patents for a company ABC Corp (ABC). A portfolio may be stored and defined as a patent set in the patent set database (e.g., patent set database 222 in FIG. 2) ABC might have received information on a potential infringing product. In order to find the patent claims relevant to the product, ABC may wish to map its entire patent portfolio and use the resulting mapped portfolio to quickly find the best claims to assert in an infringement lawsuit. However, it may also be useful to map the patents of the alleged infringer. These patents may also be added to the portfolio as it is likely ABC's patents and the alleged infringer's patents will have overlapping subject matter.
The search query may help to narrow down the patent. In an example embodiment, the search query many include a regular expression. For example, if the search query is “*” all the patent claims in the patent portfolio will be displayed. Boolean expressions such as “car && dog” may also be used. In some example embodiments, an option is included to only search independent claims, dependent claims, or to search both. In some example embodiments, the portfolio may further be narrowed by using patent concepts that have been included in the current ontology.
FIG. 12 shows an example user interface with example options available to search by technology category. An example option is presented allowing a user to search technology categories disjunctively or conjunctively. In an example embodiment, each technology category in the ontology is shown to the user with three example options “Direct mapped claims,” “Direct Mapped or ‘Does Not Map,’” and “Direct Mapped or ‘Unresolved.’” These terms will be discussed in greater detail with respect to block 1010.
FIG. 13 shows an example user interface with example options available to search by scope concept. In an example embodiment, each scope concept in the ontology is shown to the user with four example options “Direct mapped claims,” “Do not include Direct Mapped or ‘Does Not Map,’” “Direct Mapped or ‘Does Not Map,’” and “Direct Mapped and ‘Unresolved.’” These terms will be discussed in greater detail with respect to block 1010.
Referring back to FIG. 10, in an example embodiment at block 1006, the first portfolio is searched as a function of the search query. At block 1008, in an example embodiment, search results 918 are generated, the search results including one or more patent claims associated with the search query. Using the search query provided, a query may be formatted as an SQL query or other suitable format to query the underlying databases. Generating the search results may include retrieving patent claims which include terms from the search query and synonyms of the terms as well as plural versions of terms in the search query. The results of the query may then be presented to the user in an example user interface as shown in FIG. 9. Only one patent claim is illustrated, however, more patent claims may have resulted from the search and may be shown simultaneous as to have the ability to manipulate multiple patent claims. Column headings may include four radio buttons 920 signifying the options available for mapping, the matter number, the claim number, the claim text, and other technology categories or scope concepts currently mapped to the claim. Because the generated search results are searching an entire portfolio of patents it may be possible that not all of the claims of a given patent will match to the search query. A trio of numbers 922 may also be displayed for each claim in relationship to the technology category heading and the scope concept heading. These represent the nature of the relationship between the claim and the technology category or scope concept. For example, as illustrated, claim 1 has two technology categories directly mapped: “space vehicle” and “Electric Device or Method.” It also has one scope concept directly mapped.
Referring back to FIG. 10, at block 1010, in an example embodiment, a plurality of patent claims are mapped to a patent concept. In an example embodiment, in addition to the database of patents and patent portfolios, a database of patent claims may be maintained. The database of patent claims may be administered and interacted with using a DBMS as described above. As described more fully with reference to FIG. 3, each patent claim may have one or more patent concepts that have been mapped to the claim. As discussed above with reference to narrowing down search results, the relationship between a patent concept and a patent claim may take on many forms. For example, the relationship may be one where the patent concept is directly mapped to a patent claim. This may indicate that a user who looked at the claim made the decision that the patent claim was in a particular technology category, for example. Another relationship may indicate that a patent concept is not mapped to a patent claim. If a user is sure that a particular claim is not in a technology category, for example, it may be beneficial for that information to be saved so that the mapping process is not unnecessarily duplicative.
With reference back to FIG. 9, a user may select one or more patent claims to map based on the radio buttons displayed. In an example embodiment, there are four radio buttons indicating options for the claim: “Direct Mapped,” “Does Not Map,” “Unresolved,” and “No Operation.” The first two options are described in detail above. The “Unresolved” radio button may indicate that a user is not sure whether the concept should be mapped to the patent claim. This may be helpful in cases where the user does not have the legal or technical expertise to make a decision one way or another. A more senior user may then review the unresolved patent claims en masse at a later time. The last radio button may indicate that a user does not wish to have any relationship defined between the patent claim and a patent concept. In an example embodiment the “No Operation” radio button is selected by default for all the patent claims returned from the search query.
Upon a user indicating a preferred mapping for each patent claim, a user may further indicate a preference of which category of patent concept to map. In an example embodiment, there are two categories: technology categories and scope concepts (e.g., elements 924 & 926 in FIG. 9). In an example embodiment, a user clicks on the button corresponding to their preference and this preference is sent to the service device which detects the category of concept the user clicked. In response, a user interface is presented to the user corresponding to his or her preference. For example, FIG. 14, may be presented.
FIG. 14 illustrates an example search box 1402 and an example search results 1404 section. Across the top is an option to add a new patent concept 1406 (see FIG. 15 for a more detailed look at an example method to add a patent concept). Other options may include returning to the main mapping screen (e.g. FIG. 9) or canceling the mapping. In an example embodiment, the search box allows a user to search across an entire ontology for potential patent concepts. Similar to searching for patent claims, a user may enter a regular expression such as ‘*’ to retrieve all the concepts included in the present ontology. For example, the results of the search 1404 displayed in FIG. 14 only returns “multiple blades.” A checkbox is presented allowing a user to select the concept 1408. If there is more than one concept displayed a user may select more than one of the concepts by selecting the respective checkboxes next to the patent concepts. A checkbox at the top of the results may be selected if a user wishes to select all 1410 of the concepts returned from the ontology search.
Further example options may be presented to the right of each concept. An option to “modify and map” 1412 may be selected if the user wishes to modify the concept. This may be useful if a user wishes to broaden the concept so that it may be mapped to more patent claims. For example, a narrow technology category may have been defined as “power computer speakers.” Rather than a user defining a new technology category of “passive computer speakers,” the user might decide it makes more logical sense to only have one technology category titled “computer speakers.” In an example embodiment, the user can safely select “modify and map” and change the technology category to “computer speakers.” This may safely be done because all “powered computer speakers” are also “computer speakers.” In an example embodiment, every patent claim, regardless of which portfolio(s) it may be included in, will be updated to reflect the modified concept. Thus, it may not be advisable to narrow a concept without being certain every patent claim in the system adheres to the modified concept. In an example embodiment, a warning may be displayed to the user explaining the effects of modifying a concept.
In an example embodiment, an indication of a relationship between the patent concept and the plurality of claims in the database of patents may be stored (e.g., updating one or more databases). This may be accomplished, for example, by the user selecting the map button as displayed in FIG. 14. As discussed above, a user may have selected multiple patent claims resulting from searching and may have further indicated a preference for one or more patents claims to have concepts directly mapped as well as indicated a preference to have one or more patent claims have patent concepts not mapped. Thus, in an example embodiment, the indication of the relationship may include an indication that the plurality of patent claims are not mapped to the patent concept. In an example embodiment, the indication of the relationship includes an indication that the plurality of patent claims are mapped to the patent concept.
- Report and Chart Generation
It some example embodiments mapping a plurality of patent claims to a patent concept includes defining the patent concept. Defining the patent concept may be initiated by a user clicking on the example “add_new” button 1406 as displayed in FIG. 14. An example user interface that may be presented to the user in response to this selection is illustrated in FIG. 15. Two example options may be presented, “Save” and “Cancel.” Also shows are two input text boxes, “Concept Name” and “Description.” The concept name may be the actual concept and may be, for example, either a technology category or a scope concept. A user may indicate which category of patent concept the new concept belongs using a pull down menu. The user may further wish to add the concept to an existing ontology by selecting one or more ontologies as presented in FIG. 15.
As described, the system may allow the generation of visual representation of the data included in the databases to further maximize the value of concepts to patent claims. In some example embodiments the charts may be interactive. In some example embodiments, a method to generate the charts includes formulating a query to send to one or more databases, the query requesting whether or not a set of patent claims have been mapped to a set of patent concepts. An additional query may be sent to the databases to determine additional metadata about the patent claims including, but not limited to, the filing data and owner of each patent. Ranking data may be received for each patent concept retrieved from the databases. In an example embodiment, the system generates a relationship between a ranking, a patent concept, and a patent claim and displays the relationship to the user in the form of a chart. The ranking data may be stored in the database or may be received from a user. In some embodiments, ranking data may include integer values of disparate range (e.g., 1-10 or 1-100) alphabetical letters (e.g., a grading scale of A-F), or any other means to characterize a claim or concept.
In an example embodiment, a competitor landscape chart may be generated. An example simple competitor landscape chart is shown in FIG. 16. Shown is the title, patent number, filing data, total claims, each independent claim, and owner of each patent in a patent set. The patent set may reflect the patents owned by the competitors of a company requesting the map. The scope concepts that have been mapped to the patent claims in the patent set may be displayed as rows in the chart. If a scope concept has been mapped to a patent claim than the intersecting cell between the patent claim and concept may be filled in, checked, change color, patterned, shaded or otherwise have an indication of the mapping. Additional columns may indicate the competitor that first introduced a concept as well as the date it was introduced. This may be determined by examining each patent that has a concept mapped to at least one of the claims and examining the dates of each of the matching patents. In addition, the scope concepts may be sorted by frequency. Each competitor may be assigned a color or other designation such that a user may quickly determine which company owns each patent as well as who introduced what concepts first.
In an example embodiment, a product coverage chart may be generated. An example product coverage chart is shown in FIG. 17. As with FIG. 16, relevant patent information for patents included in the patent set is displayed. Also, displayed is a column titled “Has Feature?” This column may have values ranging from one to three signifying the degree to which the product includes the concept. For example, a value of three may mean the product definitely includes the concept and a value of one means the product definitely does not relate to the concept. Based on these values, the chart may dynamically update and determine values for the claim coverage and product coverage rows. For example, SC 1 and SC 5 both have a rating of ‘3’ and are present in all of the claims of patent “Title 1.” Thus, “Title 1” has a claim coverage of ‘3’ and a product coverage value of “potentially applies.” It is only “potentially applies” because it cannot be known for certain whether the patent applies but only that that SC 1 and SC 5 are present in the claims. However, because scope concepts always describe limitations, if a claim has two scope concepts mapped, as shown with respect to the claims in patent “Title 2,” the lowest ratings score will control the claim coverage. As shown, SC 6 is described as not being present in the product and the “Title 2” claims have been mapped to SC 6. Therefore, regardless of the fact the SC 3 has also been mapped and the product has this feature, the “Title 2” claims cannot apply to the product as they are at least limited to SC 6.
This chart may also allow interactivity with a user. This interactivity may include the user changing the “Has feature” values and the chart automatically updating the claim coverage and product coverage rows. For example, if the SC 1 rating was changed to ‘1,’ the claim coverage value of the patent “Title 1” may change to “1” signifying the patent does not apply to the product. In some embodiments, any changes that result from input from the user are highlighted on the chart. This may allow a user to quickly see the effects of potential changes to product coverage.
FIG. 18 illustrates an example freedom to operate chart. In an example embodiment, a freedom to operate chart allows a user to quickly see which patents may be necessary to obtain licenses from or purchase to produce a product, sell a service, etc. FIG. 18 is similar to FIG. 17 except for in place of a “Has feature?” column there is a “Need Feature?” column The values in this column may represent whether or not, and to what extent, a user believes a feature is necessary in his or her product. A ‘3’ may indicate that the scope concept is necessary, a ‘2’ may indicate the scope concept is wanted, but not needed, and a ‘1’ may indicate the scope concept is not needed. In an example embodiment, the “claim status” row shown in FIG. 18 reflects whether a patent in the patent set needs to be licensed or purchased in order for the user to operate freely. As with the product coverage chart, the lowest value in the “need feature” column controls. Thus, patent “Title 1” is not needed even though SC 1 is mapped to all the claims and the user has indicated the feature is necessary. Similarly to above, a user may interact with the ratings to see in real-time the impact of removing or adding features in terms of the number of patents needing to be licensed or purchased.
FIG. 19 illustrates an example claim/patent valuation chart. In an example embodiment, a claim/patent valuation chart allows a user to see which patents/claims may be necessary to license, etc., to maximize the value of a currently owned patent or patent claim. FIG. 19 is similar to FIG. 17 except the values in the ratings column reflect whether or not a scope concept is necessary to maximize a patent's value. The values in this column may represent whether or not, and to what extent, a user believes a feature is necessary in maximize a patent's value. A ‘3’ may indicate that the scope concept is necessary, a ‘2’ may indicate the scope concept is wanted, but not needed, and a ‘1’ may indicate the scope concept is not needed. In an example embodiment, the “claim value” row shown in FIG. 19 reflects whether a patent in the patent set needs to be licensed or purchased in order to maximize the user's patent. As with the product coverage chart, the lowest value in the rating column controls. Thus, patent “Title 1” is not important, even though SC 1 is mapped to all the claims and the user has indicated a high value for SC 1. Similarly to the above charts, a user may interact with the chart by changing the ratings to see in real-time the effects on patents in the patent set.
FIG. 20 illustrates an example validity chart. In an example embodiment, a validity chart allows a user to see the overlap between a patent and a patent set. FIG. 20 is similar to FIG. 17 except the values in the ratings column reflect whether or not a feature is shown in the patent in question (the patent to which the patent set is being compared). The values in this column may represent whether or not, and to what extent, a user believes a feature is present in the patent in question. A ‘3’ may indicate that the scope concept is shown, a ‘2’ may indicate the scope concept is possibly shown, and a ‘1’ may indicate the scope concept is not shown. In an example embodiment, the claim status row shown in FIG. 20 reflects the extent to which the patent in question and the patents in the patent set overlap. Unlike the product coverage chart, if two scope concepts are mapped to a patent, but contain different ratings, the feature rating becomes “some overlap”. Thus, even though SC 5 has been rated as not shown and mapped to patent “Title 1,” SC 1 is also mapped to the patent but is shown and therefore there is some overlap between the patent in question and patent “Title 1.” A finding of “complete overlap” may indicate to a user that a patent or claim is completed anticipated. As above, the user may interact with the chart by changing the ratings to see in real-time the effects on patents in the patent set.
- Computer System
FIG. 21 illustrates an example white space analysis chart. In an example embodiment, a white space analysis chart allows a user to see the frequency in which scope concepts appear in a patent set. In some embodiments there are scope concepts that are in no patent claims. The chart may be color coded to allow a user to quickly ascertain the least frequently used scope concepts. FIG. 22 illustrates an example white space claim generation chart. In an example embodiment the generated chart illustrates suggested combinations of unclaimed combinations of existing scope concepts as well as suggested combinations of new scope concepts with existing scope concepts.
FIG. 23 shows a diagrammatic representation of a machine in the example form of a computer system 2300 within which a set of instructions for causing the machine to perform any one or more of the methodologies discussed herein may be executed. In alternative embodiments, the machine operates as a standalone device or may be connected (e.g., networked) to other machines. In a networked deployment, the machine may operate in the capacity of a server or a client machine in a server-client network environment or as a peer machine in a peer-to-peer (or distributed) network environment. The machine may be a Personal Computer (PC), a tablet PC, a Set-Top Box (STB), a Personal Digital Assistant (PDA), a cellular telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein. Example embodiments can also be practiced in distributed system environments where local and remote computer systems which are linked (e.g., either by hardwired, wireless, or a combination of hardwired and wireless connections) through a network both perform tasks. In a distributed system environment, program modules may be located in both local and remote memory-storage devices (see below).
The example computer system 2300 includes a processor 2302 (e.g., a Central Processing Unit (CPU), a Graphics Processing Unit (GPU) or both), a main memory 2304 and a static memory 2306, which communicate with each other via a bus 2308. The computer system 2300 may further include a video display unit 2310 (e.g., a Liquid Crystal Display (LCD) or a Cathode Ray Tube (CRT)). The computer system 2300 may also includes an alphanumeric input device 2312 (e.g., a keyboard), a User Interface (UI) cursor controller (e.g., a mouse), a disc drive unit 2316, a signal generation device 2318 (e.g., a speaker) and a network interface device (e.g., a transmitter) 2320.
The disc drive unit 2316 includes a machine-readable medium 2328 on which is stored one or more sets of instructions 2317 and data structures (e.g., software) embodying or utilized by any one or more of the methodologies or functions illustrated herein. The software may also reside, completely or at least partially, within the main memory 2304 and/or within the processor 2302 during execution thereof by the computer system 2300, the main memory 2304 and the processor 2302 also constituting machine-readable media.
The instructions 2317 may further be transmitted or received over a network (e.g., the INTERNET) 2326 via the network interface device 2320 utilizing any one of a number of well-known transfer protocols (e.g., HTTP, Session Initiation Protocol (SIP)).
The term “machine-readable medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term “machine-readable medium” shall also be taken to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by the machine and that cause the machine to perform any of the one or more of the methodologies illustrated herein. The term “machine-readable medium” shall accordingly be taken to include, but not be limited to, solid-state memories, and optical and magnetic medium.
The Abstract of the Disclosure is provided to comply with 37 C.F.R. §1.72(b), requiring an abstract that will allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separate embodiment.