FR3093202A1 - PROCESS FOR DETERMINING A BEHAVIORAL DIAGRAM - Google Patents

Abstract

METHOD OF DETERMINING A BEHAVIORAL SCHEME A method of determining a behavioral pattern of a patent manager (301, 307, 308, 309) which comprises the following steps: - definition (11) of a first patent application (301) defined at least by, a unique identifier (302), a holder (303) and classes (305, 306), - evaluation (12) of an associated technical field (305) according to each class, - matching (26) of at least one economic value corresponding to at least one geographical area (301) for the technical field, and at least one phase among, on the one hand: - association (16) of at least one other request (308, 309) from the same technical field and / or to the holder, - determination (19, 24) of at least one geographical extension scheme of the other titles; and on the other hand, - definition (27) of a predetermined limit value (311), - classification (28) of the economic data by decreasing value, - calculation (29) of the sum of each economic data until exceeding at the predetermined limit value, and - determination (30) of a geographical extension pattern depending on the economic values. Figure for abstract: figure 3

Description

PROCEDURE FOR DETERMINING A BEHAVIORAL PATTERN

The present invention relates to a method for determining a behavioral pattern of a user of a database of at least two industrial property titles. It applies, in particular, to the recognition and comparison of behavioral patterns in terms of the geographical extension of industrial property titles.

Currently, portfolio managers of industrial property titles, and in particular patents, manage geographical extensions, for example, the exit from the international phase of the Patent Cooperation Treaty (acronym " PCT " for " Patent Cooperation Treaty in English), empirically. That is to say that a use has been established by the experience of managers without the possibility of evaluating the quality or the influence of the choices made.

In addition, geographical extensions, which require translations, the payment of taxes and the intervention of advice, represent a considerable investment for companies.

Managers of portfolios of industrial property titles can also rely on the suggestions given by their advisers who can assess the legal solidity of the title. However, the councils are not experts in the markets targeted by the companies.

Thus, portfolio managers of industrial property titles lack objective evaluation criteria as to quality, profitability and/or the potential market protected when making choices.

The present invention aims to remedy all or part of these drawbacks.

To this end, the present invention relates to a method for determining a behavioral pattern of a user of a database of at least two industrial property titles, which comprises the following steps:

- definition of a first industrial property title defined, in a first database at least by, computer data representative of a unique identifier, computer data representative of a holder of the title called "holder" and computer data representative of at least one technical class called "class",

- evaluation of a technical field associated with the first industrial property title according to each class,

- matching of at least one piece of data representative of an economic value corresponding to at least one geographical area, called "zone economic data", stored in a second database, for the determined technical field,

and at least one phase from:

- a first phase of recognition according to the data of the first database comprising the following steps:

- association of at least one other industrial property title from the first database corresponding to the evaluated technical field of the first industrial property title and/or to the holder of the title,

- determination of at least one geographic extension behavioral pattern based on each other associated industrial property title;

- a second phase of recognition according to the data of the second database comprising the following steps:

- definition of a predetermined limit value,

- ranking of each zone economic data matched by decreasing value,

- an iterative step of calculating the sum of each zone's economic data, in order of classification, until the value of the sum is greater than or equal to the predetermined limit value, and

- determination of a geographic extension behavioral scheme depending on the list of geographic areas whose economic area data was used during the last iteration of the calculation step.

Thanks to these provisions, the behavior of managers in similar situations is studied and makes it possible to deduce, for the manager in charge of the industrial property title studied, an appropriate strategy according to the behaviors observed to limit costs and optimize the decisions taken.

In embodiments, the step of evaluating the technical field of the first title comprises:

- a truncation step of each class to obtain a truncated class and

- a step for counting the number of occurrences of classes with the same truncation, the technical field evaluated corresponding to the truncated class with the majority number of occurrences.

These embodiments make it possible to identify a broader technical field than the strict one of the invention.

In embodiments, the step of evaluating the technical field is applied to each other title of the first database presenting an equivalent holder.

The advantage of these embodiments is to identify a large number of titles of similar technical fields to obtain a behavioral study on a sufficient sample.

In embodiments, the step of evaluating the first title comprises, when an equality of the number of occurrences for at least two truncated classes is detected, a step of counting the number of occurrences of each truncated class among each another title from the first database with an equivalent holder.

These embodiments make it possible to decide between the truncated classes of numbers of equal occurrences in order to identify a technical field of the invention.

In some embodiments, during the first recognition phase, the step of determining a behavioral pattern of determined geographical extension called "habit doctrine" comprises:

- a step of counting the number of occurrences of a geographical area for each industrial property title of the first database of equivalent holder and of the same technical field and

- a classification step for each geographical area by decreasing number of occurrences.

These embodiments make it possible to identify the manager's past choices in relation to other similar securities.

In some embodiments, during the first recognition phase, the step of determining a behavioral pattern of determined geographical extension called "comparison doctrine" comprises:

- a step for counting the number of occurrences of each holder of at least one industrial property title from the first database,

- a step of selecting a predetermined value of at least one holder classified by decreasing number of occurrences,

- a step of counting the number of industrial property titles of the first database of the same technical field for each holder selected,

- a classification step for each zone by decreasing number of occurrences.

Thanks to these provisions, similar behaviors of other managers are identified.

In embodiments, a step of filtering each holder according to the nationality of the holder.

The advantage of these embodiments is to study a behavior according to the origin of different competitors.

In some embodiments, the method that is the subject of the present invention comprises a step of displaying at least one behavioral diagram of determined geographical extension.

These embodiments make it possible to graphically represent the observed behaviors.

In some embodiments, the method that is the subject of the present invention comprises, for at least one determined behavioral pattern, a step of classifying each geographical extension zone by decreasing zone economic data.

Thanks to these provisions, a ranking of the most frequent choice to the least frequent is carried out.

Other advantages, aims and particular characteristics of the invention will emerge from the non-limiting description which follows of at least one particular embodiment of the method which is the subject of the present invention, with reference to the appended drawings, in which:

represents, schematically and in the form of a flowchart, a particular succession of steps of the method which is the subject of the present invention,

represents, schematically and in the form of a flowchart, a continuation of the particular succession of steps of the method which is the subject of the present invention represented in FIG. 1 and

represents, schematically, a graphic representation of the objects manipulated by the method which is the subject of the present invention.

DESCRIPTION OF EXAMPLES OF EMBODIMENT OF THE INVENTION

This description is given on a non-limiting basis, each characteristic of an embodiment being able to be combined with any other characteristic of any other embodiment in an advantageous manner.

Note that the figures are not to scale.

In FIGS. 1 and 2, a succession of steps of an embodiment of the method, 100 and 200, which is the subject of the present invention, can be seen.

The method for determining, 100 and 200, a behavioral pattern of a user of a database of at least two titles, 301, 307, 308 and 309, of industrial property comprises a step 11 of defining a first industrial property title 301 defined, in a first database at least by, computer data representative of a unique identifier 302, computer data representative of a holder of the title called "holder" 303 and computer data representative at least one technical class called "class", 305 and 306.

• une première partie représentative d’une zone géographique, comportant au moins deux lettres, par exemple, lorsque la zone géographique à représenter est un pays, les lettres correspondent à celles du code ISO 3166-1 Alpha 2 et
• une deuxième partie comportant une identification numérique incrémentale d’un titre à l’autre en fonction d’une date, par exemple, la date de dépôt, de priorité ou de publication.

The industrial property title is preferably a patent application or a granted patent. The unique identifier is a series of alphanumeric characters presenting:

• a first part representative of a geographical area, comprising at least two letters, for example, when the geographical area to be represented is a country, the letters correspond to those of the ISO 3166-1 Alpha 2 code and
• a second part comprising an incremental numerical identification from one title to another according to a date, for example, the date of filing, priority or publication.

In embodiments, the unique identifier corresponds to the publication number, application number or grant number of a patent or patent application.

Each industrial property title of the first database comprises a field representative of the geographical area, country or region, covered by the title.

The computer data representative of a holder may represent a name, an address, a telephone number, a legal form, a unique identification number issued by a government administration, and/or any other information representative of a company or of an individual.

• une lettre représentative d’une section,
• deux chiffres représentatifs d’une classe,
• une deuxième lettre représentative d’une sous-classe ;
• au moins un chiffre représentatif d’un groupe.

Each computer data representative of at least one technical class may correspond to a patent classification such as the "Cooperative Patent Classification" (acronym "CPC") or the "International Patent Classification" (acronym "IPC") . Each code representing a technical field of the CPC and the IPC includes at least, in the following order:

• a letter representing a section,
• two figures representing a class,
• a second letter representing a subclass;
• at least one figure representative of a group.

In some embodiments, each code further comprises at least two other digits separated from each digit representing a group by the symbol “ / ”. Said other two digits represent a subgroup. For example, the alphanumeric string of data representative of a technical class would be "A21C1/06".

• d’un mandataire,
• d’un numéro de priorité,
• d’une date de priorité,
• de l’identification d’un inventeur,
• d’une date de dépôt,
• d’un numéro de dépôt,
• d’une date de publication,
• d’un numéro de publication, et/ou
• de toute autre information connue de l’homme du métier et présente sur au moins base de données de titres de propriété industrielle.

In embodiments, for each title, the first database also includes one or more representative digital data:

• of an agent,
• a priority number,
• a priority date,
• the identification of an inventor,
• a filing date,
• a deposit number,
• a date of publication,
• a publication number, and/or
• any other information known to those skilled in the art and present on at least a database of industrial property titles.

During the definition step, a first industrial property title is identified, for example by the unique identifier. The definition step can be carried out by means of a man/machine interface known to those skilled in the art, on a communicating terminal connected to at least one server comprising the first database.

The method, 100 and 200, comprises a step 12 of evaluating a technical field associated with the first title 301 of industrial property as a function of each class, 305 and 306. Each class, 305 and 306, gives information concerning a field technique to which the industrial property title applies. Evaluation step 12 makes it possible to deduce the predominant technical domain.

Preferably, the evaluation step 12 of the technical field 305 of the first title 301 includes:

- a truncation step 13 of each class, 305 and 306, to obtain a truncated class,

- a counting step 14 of the number of occurrences of classes, 304 and 305, of the same truncation, the technical field evaluated corresponding to the truncated class of majority number of occurrences.

In truncation step 13, each class is truncated such that the subclass is the last element considered. For example, the class "A21C1/06" is shortened to "A21C". The truncation step is performed by computer, for example by means of an application server interrogating the first database to retrieve each class. In embodiments, the class, 305 or 306, may be abbreviated to digits representative of the class. For example, the class "A21C1/06" is shortened to "A21".

Then, for the industrial property title, we count the number of classes which, once truncated, are identical. To carry out the calculation by computer, a sorting algorithm known to those skilled in the art can be used.

The technical domain evaluated corresponds to the technical domain of the truncated class appearing the greatest number of times.

Preferably, the evaluation step 12, the truncation step 13 and the counting step 14 are applied to each other title, 307 and 308, of the first database presenting an equivalent holder.

The term equivalent holder refers to holders whose name is the same and/or whose unique national identifier, for example the number of the business directory identification system (acronym " SIREN ") is the same.

In embodiments, the method, 100 and 200, includes a step of standardizing the computer data representative of holders stored in the first database. The standardization step can, for example, put each character in lowercase, remove special characters, remove accents.

In some embodiments, in the event of equality between the number of occurrences, the step 12 of evaluating the first title 301 comprises, a step 15 of counting the number of occurrences of each truncated class among each other title, 307 and 308, of the first database presenting an equivalent holder 303 . Then, the truncated class is stored in a field of the first database.

The counting step 15 can be implemented by means of a sorting algorithm, similar to step 14, applied to each class of each title, 307 and 308, presenting an equivalent holder 303. Then, the truncated class is stored in a field of the first database. Preferably, each truncated class is taken into account independently of the title, 307 or 308, with which the class is associated.

The method, 100 and 200, implements at least one phase from among a first recognition phase, 101 and/or 102, and a second recognition phase 103.

Each first phase of recognition, 101 and/or 102, is implemented according to the data of the first database.

Each first phase of recognition, 101 and/or 102, comprises a step 16 of association of at least one other title, 307, 308 and/or 309, of industrial property of the first database corresponding to the technical field 305 evaluated of the first industrial property title 301 and/or to the holder 303.

To associate 16, at least one industrial property title 309 of technical field corresponding to the technical field of the first title 101, the evaluation step 12 is applied to each title of the first database. Then, the technical domain is stored in a field of the first database. During the association step, a filter according to the evaluated technical field of the first title 301 is applied.

In embodiments, each evaluation step is carried out prior to the recognition phases. And the field corresponding to the evaluated technical field is updated during updates of at least one class associated with a title of the first database.

Each phase of recognition, 101 or 102, comprises a step of determination, 19 or 24, of at least one behavioral pattern of geographic extension as a function of each other associated title of associated industrial property. The determination phase is carried out automatically and by computer.

During phase 101, step 19 for determining a behavioral pattern of determined geographical extension called "habit doctrine" includes:

- a counting step 17 of the number of occurrences of a geographical area for each industrial property title 308 of the first database of equivalent holder and of the same technical field and

- a classification step 18 of each geographical area by decreasing number of occurrences.

During the counting step 17, the content of the field comprising the geographical area covered by the title is subjected to a sorting algorithm known to those skilled in the art to count 17 and classify 18 the geographical areas by decreasing number of occurrences . The ranking is temporarily stored.

During the phase 102, the step 24 for determining a behavioral pattern of determined geographical extension called "comparison doctrine" comprises:

- a counting step 20 of the number of occurrences of each holder of industrial property titles in the first database,

- a selection step 21 of a predetermined value X of holders classified by decreasing number of occurrences,

- a counting step 22 of the number of industrial property titles of the first database of the same technical field for each holder selected,

- a classification step 23 of each zone by decreasing number of occurrences.

The counting step 20 is carried out similarly, to the counting steps 15 and 17, by a sorting algorithm. During the selection step, an operator specifies, by means of a man/machine interface, for example a keyboard, a mouse or a touch screen, the number of holders X to be taken into account. In embodiments, a choice of predetermined values X can be offered to the user, for example, three, five or ten.

During counting step 20, the corresponding holders are considered to be the same holder.

The X most recurring holders are selected. A filtering of the first database is performed to exclude holders other than the selected holders.

Then for each title of at least one of the X selected holders, a counting step 22 is implemented similar to the counting step 17 and independent of the holder of the title.

The behavioral pattern determined, in the first phase, 101 and/or 102, corresponds to the most recurrent geographical areas classified by decreasing recurrence. The sorted list is stored in a memory at least temporarily.

In some embodiments, the method 100 or 200 comprises a step of filtering each holder according to the nationality of the holder.

The nationality of the holder can be entered in a field of the first database, in a third database, or consultation of a field containing information on the country of origin of the holder.

The method, 100 and 200, also includes a step of matching at least one piece of data representative of an economic value corresponding to at least one geographical area, called "zone economic data", stored in a second database , for the given technical field.

The economic value is preferably a value from at least one government database.

The step of automated matching based on descriptive character strings, the technical field, on the one hand, and the economic value, on the other hand.

The second phase of recognition 103 according to the data of the second database 310 comprising the following steps:

- definition 27 of a predetermined limit value 311,

- ranking 28 of each zone economic data matched by decreasing value,

- an iterative step 29 of calculation of the sum of each zone economic datum, by order of classification, until the value of the sum is greater than or equal to the predetermined limit value 311, and

- determination 30 of a geographic extension behavioral scheme depending on the list of geographic areas whose economic area data was used during the last iteration of the calculation step 29.

During the definition step 27, an operator enters a predetermined limit value by means of a man/machine interface, for example by moving a slider representing a target market percentage ranging from zero percent to one hundred percent. The first predetermined limit value 311 is then calculated from the market value over all the geographical areas.

During the classification step 28, a sorting algorithm is implemented to classify the geographical areas according to the value of the economic data in a decreasing manner. The classification step 28 is preferably implemented by an application server.

During the calculation step 29, it is checked whether the value of the geographical area classified according to the first rank is greater than the predetermined limit value 311. If so, one proceeds to the determination step 30. Otherwise, one calculates the sum of the economic value corresponding to the geographical area ranked first with the economic value corresponding to the geographical area ranked second. If the sum is greater than the predetermined limit value 311, the procedure proceeds to the determination step, otherwise the calculation is repeated with the economic value corresponding to the geographical area of the third rank. The calculation step 29 is iterated until the sum is greater than the predetermined limit value 311.

The behavioral pattern determined, in the second phase 103 corresponds to the most recurrent geographical areas classified by decreasing recurrence. The sorted list is stored in a memory at least temporarily.

In embodiments, the method, 100 and 200, includes a step 31 of displaying each behavioral pattern of determined geographical extension.

The display 31 is preferably produced on a screen, for example, by means of an internet browser displaying a secure internet page by using the behavioral patterns calculated by an application server. The display 21 can be in the form of a map or a list, for example.

In some embodiments, the method 100 and 200 comprises, for at least one determined behavioral pattern, 101, 102 and/or 103, a step 32 of classifying each geographical extension zone by decreasing zone economic data.

Each behavioral pattern, 101, 102 and/or 103, returns a list of geographic areas, each geographic area is mapped to an economic value. The classification step 32 carries out the classification by decreasing value of the economic values associated with the geographical areas. The classification step can be implemented by an application server implementing a sorting algorithm.

Claims (9)

Method (100 and 200) for determining a behavioral pattern of a user of a database of at least two titles (301, 307, 308, 309) of industrial property, characterized in that it comprises the following steps :
- definition (11) of a first industrial property title (301) defined, in a first database at least by, computer data representative of a unique identifier (302), computer data representative of a holder of the title called "holder" (303) and computer data representative of at least one technical class called "class" (305, 306),
- evaluation (12) of a technical field (305) associated with the first industrial property title according to each class,
- matching (26) of at least one piece of data representative of an economic value corresponding to at least one geographical zone, called "zone economic data" (310), stored in a second database, for the technical field determined,
and at least one phase from:
- a first phase (101, 102) of recognition according to the data of the first database comprising the following steps:
- association (16) of at least one other industrial property title (308, 309) from the first database corresponding to the evaluated technical field of the first industrial property title and/or to the holder of the title,
- determination (19, 24) of at least one behavioral pattern of geographic extension as a function of each other associated title of associated industrial property;
- a second recognition phase (103) based on data from the second database comprising the following steps:
- definition (27) of a predetermined limit value (311),
- ranking (28) of each zone economic data matched by decreasing value,
- an iterative step of calculation (29) of the sum of each zone economic datum, by ranking order, until the value of the sum is greater than or equal to the predetermined limit value, and
- determination (30) of a geographic extension behavioral scheme depending on the list of geographic areas whose economic area datum was used during the last iteration of the calculation step. A method (100, 200) according to claim 1, wherein the step of evaluating (12) the technical field (305) of the first title comprises:
- a truncation step (13) of each class (305, 306) to obtain a truncated class and
- a counting step (14) of the number of occurrences of classes of the same truncation, the evaluated technical field corresponding to the truncated class of majority number of occurrences. Method (100, 200) according to claim 2, in which the step of evaluating (12) the technical field (305) is applied to each other title (307) of the first database having an equivalent holder. Method (100, 200) according to claim 3, in which the step of evaluating (12) the technical field of the first title (301) comprises, when an equality of the number of occurrences for at least two truncated classes is detected, a step of counting (15) the number of occurrences of each truncated class among each other title (307) of the first database presenting an equivalent holder. Method (100, 200) according to claims 1 to 4, in which during the first phase (101) of recognition, the step of determining (19) a behavioral pattern of determined geographical extension called "habit doctrine » includes:
- a step of counting (17) the number of occurrences of a geographical area for each title (307) of industrial property of the first database of owner (303) equivalent and of the same technical field (305) and
- a classification step (18) of each geographical area by decreasing number of occurrences. Method (100, 200) according to one of Claims 1 to 5, in which during the first phase (102) of recognition, the step of determining a behavioral pattern of determined geographical extension, known as the "comparison doctrine" includes:
- a counting step (20) of the number of occurrences of each holder of at least one industrial property title from the first database,
- a selection step (21) of a predetermined value of at least one holder classified by decreasing number of occurrences,
- a counting step (22) of the number of industrial property titles (309) of the first database of the same technical field (305) for each holder selected,
- a classification step (23) of each zone by decreasing number of occurrences. Method (100, 200) according to claim 6, which comprises a step of filtering (25) each holder according to the nationality of the holder. Method (100, 200) according to one of Claims 1 to 7, which comprises a step of displaying (31) at least one behavioral diagram of determined geographical extension. Method (100, 200) according to one of Claims 1 to 8, which comprises, for at least one determined behavioral pattern, a step of classifying (103) each geographical extension zone by decreasing zone economic data.