Method, device, processor and computer readable storage medium for generating a record associating a business mail with an order

Abstract

The application relates to a business mail associated order record generation method and device, a processor and a computer readable storage medium thereof. The method adopts the application, and the method is used for matching each associated order of each target mail from an order pool in response to the content of the target mail; determining a target mail set associated with each associated order based on each target mail and each associated order; generating mail history content of the associated order based on the preset dimension based on each associated order and the target mail set associated with the associated order; and generating a back-and-forth communication record of the associated order based on the mail history content. In the case that an explicit order number is missing, a title is repeatedly modified or a business personnel uses a non-standard expression, the association relationship between the mail and a candidate existing order can be determined, the scattered mails are arranged into the communication record of the order, the mails are precipitated from the communication tool into the order performance data, and thus the back-and-forth communication record of the associated order is generated.

Description

Technical Field

[0001] This invention relates to the field of email processing, specifically to a method, apparatus, processor, and computer-readable storage medium for generating records of business email-linked orders. Background Technology

[0002] In cross-border foreign trade logistics, freight forwarding, customs declaration, overseas customs clearance, and supply chain collaboration, order fulfillment is often accompanied by a large volume of emails. These emails may simultaneously contain various types of information, including order placement requests, supplementary documentation, booking confirmations, container numbers, bill of lading numbers, customs declaration documents, inspection feedback, fee confirmations, tax invoice communication, and customs clearance status. Existing email processing methods typically rely on manual judgment, email titles, fixed keywords, attachment templates, or simple rules. These methods struggle to reliably identify the actual business order corresponding to an email when there are inconsistent email titles, long historical reply chains, multiple forwardings, numerous attachments, a single email involving multiple orders, business personnel omitting order numbers, or different customers having different naming conventions. Some existing technologies can extract structured information from emails and create orders, or select parsing rules based on attachment identifiers and generate business orders. However, these solutions primarily address the issue of "email content being entered as new documents," with the output typically being new orders, new business orders, or pending records. They cannot effectively resolve issues related to the attribution, disambiguation, and contextualization of emails and order objects during existing order fulfillment processes. While simple email summarization tools can compress email content, they typically cannot resolve the issue of accurately attributing emails to orders, nor can they automatically reconstruct communications scattered across different email threads, attachment versions, and business stages into a complete business record at the order level. Therefore, the industry still needs a technical solution capable of automatically determining existing order associations, splitting multiple orders into their attribution, and organizing the context in complex business email scenarios. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method, apparatus, processor and computer-readable storage medium for generating records of business email-linked orders.

[0004] To achieve the above objectives, the present invention provides a method, apparatus, processor, and computer-readable storage medium for generating records of business email-linked orders, as follows: A method for generating records associated with business emails, characterized in that the method includes the following steps: (1) In response to the content of each target email, extract the target business event from the content of each target email; The target business events include business information of different business types; (2) Based on the target business event of each target email, match each associated order with each target email from the order pool; (3) Based on each target email and each associated order, determine the set of target emails associated with each associated order; (4) Generate the email history content of the associated orders based on each of the associated orders, the target email set associated with the associated orders, and the preset dimensions; (5) Generate the communication records of the associated order based on the email history content.

[0005] Preferably, step (1) specifically includes: (1.1) In response to the content of each target email, extract at least one business element of each target email from the content of each target email according to the first preset requirement; The business elements include business information for at least one type of business; (1.2) Based on the second preset requirement, at least one business element of the target email is combined into a target business event for each target email.

[0006] Preferably, the content of the target email includes the email body and attachments, and step (1.1) specifically includes: (1.1.1) The email body is standardized to obtain the first text; (1.1.2) Extract text from the email attachments based on their type to obtain the second text; (1.1.3) The content of the target email is determined based on the first text and the second text.

[0007] Preferably, step (2) specifically includes: (2.1) Based on the target business event of each target email, match each candidate order corresponding to each target email from the order pool; (2.2) Based on the correlation between each target email and its corresponding candidate order, determine the associated order of each target email from the candidate orders.

[0008] Preferably, step (2.2) further includes: (2.1.1) Obtain the first business information of the target email and the second business information of each order in the order pool, and exclude the orders corresponding to the second business information that do not conflict with the first business information from the candidate orders; Step (2.2) further includes: (2.2.1) Based on the correlation between each target email and each first candidate sub-order, the first candidate sub-order that exceeds the preset correlation is determined as the associated order.

[0009] Preferably, step (2.2) further includes: (2.2.2) When the associated order of the target email cannot be determined from the candidate orders, output the candidate order that matches the target order or output the suspected new business reminder corresponding to the target order; (2.2.3) When a candidate order for the target email cannot be matched from the order pool, output a suspected new business reminder corresponding to the target order.

[0010] Preferably, step (2.2) further includes: (2.2.4) When the target email has at least two associated orders, the email content of the target email is split into email content fragments, and the associated orders corresponding to each email content fragment are determined.

[0011] Preferably, the preset dimensions include at least one of the following: business element continuity, business participant relationships, business time, attachment version, and business stage.

[0012] Preferably, step (2) further includes: (2.3) Output the association results of each associated order of each target email; The method further includes the following steps: (5) Obtain feedback results of the association results, and optimize the process of matching each associated order with each target email from the order pool based on the feedback results.

[0013] The apparatus for generating records of business email-linked orders is characterized in that the apparatus comprises: A processor is configured to execute computer-executable instructions; The memory stores one or more computer-executable instructions, which, when executed by the processor, implement the various steps of the above-described method for generating records of business email-related orders.

[0014] The processor for generating records of business email-linked orders is characterized in that the processor is configured to execute computer-executable instructions, which, when executed by the processor, implement the various steps of the above-described method for generating records of business email-linked orders.

[0015] The computer-readable storage medium is characterized in that it stores a computer program thereon, which can be executed by a processor to implement the various steps of the above-described method for generating records of business email-linked orders.

[0016] The method for generating records of business emails associated with orders, as described in this invention, can determine the association between emails and existing candidate orders even when there is a lack of clear order numbers, the title has been repeatedly modified, or business personnel use non-standard expressions. It can also organize scattered emails into communication records for orders, transforming emails from communication tools into order fulfillment data, thereby generating communication records of related orders. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating one embodiment of the method for generating records of business email-linked orders according to the present invention. Detailed Implementation

[0018] To more clearly describe the technical content of the present invention, the following description is provided in conjunction with specific embodiments.

[0019] Please see Figure 1 The method for generating records of business email-linked orders according to the present invention includes the following steps: (1) Respond to the content of each target email and extract the target business event from the content of each target email; The target business events include business information from different business types.

[0020] In some embodiments, the target business event includes at least one business element, and the business element includes business information of at least one business type. In some embodiments, the business information may include categories such as customer name, freight forwarder, customs broker, order identifier, shipping identifier, document identifier, container number, vessel name and voyage number, port, destination, cargo information, cost information, anomalies, business stage, and time node. Further, the target business event may include event subject, business object, business action, time information, source location, supporting evidence, context fragment, and confidence status.

[0021] In some embodiments, different ways of expressing the same business element can be semantically normalized so that expressions in different languages, abbreviations, and business practices can be merged into a unified business semantic.

[0022] In some embodiments, the email content may include: "Manager Wang, the attachment contains the latest packing list and invoice, container number MSKU1234567, vessel name and voyage number: COSCO STAR / 087E, with an estimated cut-off date this Friday. The previously mentioned product name has been changed to LEDdesk lamp; please check if any documents are missing from the customs declaration." The email body does not directly state the order number, nor does it use a standard format. After parsing the email body, attachment file names, attachment content, and historical reply chains, the system identifies the following business elements as shown in the table below: After identifying the above business elements, the target business events can be represented as shown in the table below: (2) Based on the target business events of each target email, match the associated orders with each target email from the order pool; In some embodiments, a candidate order set is generated from the order system based on the aforementioned business elements and target business events. For example, the following three candidate orders are retrieved: (3) Based on each target email and each associated order, determine the set of target emails associated with each associated order; In the above embodiment, based on a comprehensive assessment of the customer entity, container number, vessel name and voyage number, attachment content, order status, business stage, and historical email correspondence, it is determined that order A has the highest correlation with this email and there is no obvious conflict. Therefore, the system automatically associates this email with order A and generates a "Supplement to Customs Declaration Documents" event record in the communication history of order A. The record may include: email source, communication time, customer entity, business stage, type of supplementary documents, attachment index, product name change information, customs deadline reminder, and original document location. If the business personnel subsequently confirm that the association result is correct, the system records the confirmation result; if the business personnel modify it to another order or split it into multiple orders, the system records the correction result and uses it for subsequent optimization of candidate orders for similar emails. (4) Generate the email history content of the associated orders based on each associated order, the target email set associated with the associated orders, and preset dimensions; In some embodiments, after establishing the association between emails and orders, the emails are reconstructed according to the order dimension. The reconstruction process not only relies on the original email thread, but also takes into account the continuity of business elements, the relationships between participants, the time sequence, the relationship between attachment versions, and changes in business stages, to organize the scattered emails into a single email history content oriented towards the order execution process.

[0023] Email history related to orders can be categorized by business stage, such as order placement, supplementary information, order review issues, booking confirmation, document confirmation, customs declaration, exception handling, receipt synchronization, fee confirmation, customs clearance status, or case closure and archiving. Specific stage names can be configured according to different industries or company processes.

[0024] By reconstructing the context as described above, the complete communication flow surrounding the same order can be displayed on the order details page, instead of just showing isolated emails or raw email threads. This processing result provides a structured foundation for subsequent customer service collaboration, exception handling, data tracing, and business review.

[0025] (5) Generate communication records of related orders based on email history content.

[0026] In some embodiments, business communication records for related orders are automatically generated based on the reconstructed email history content. These communication records may include the communication time, participants, source email, business stage, summary, to-do items, exception notifications, attachment list, original email location, recommendation basis, and processing status.

[0027] The generated communication records can be displayed on the order details page, customer service workbench, exception handling page, document review page, or business review page, and support retrieval, filtering, tracing, and subsequent business collaboration.

[0028] Preferably, step (1) specifically includes: (1.1) In response to the content of each target email, extract at least one business element of each target email from the content of each target email according to the first preset requirement; The business elements include business information for at least one type of business; (1.2) Based on the second preset requirement, at least one business element of the target email is combined into a target business event for each target email.

[0029] Preferably, the content of the target email includes the email body and attachments, and step (1.1) specifically includes: (1.1.1) The email body is standardized to obtain the first text; (1.1.2) Extract text from the email attachments based on their type to obtain the second text; (1.1.3) The content of the target email is determined based on the first text and the second text.

[0030] Preferably, step (2) specifically includes: (2.1) Based on the target business event of each target email, match each candidate order corresponding to each target email from the order pool; In some embodiments, candidate orders can be obtained through one or more methods such as identifier matching, business entity matching, transportation element matching, document element matching, counter number or bill of lading number matching, time window matching, historical email relationship matching, attachment content matching, semantic similarity relationship matching, etc.

[0031] In some embodiments, it is not required that the target email contain a unique order number. Even if the target email only contains customer name, shipping information, document information, attachment content, or business description, the range of candidate orders can be determined based on at least one of the above matching methods.

[0032] In some embodiments, the system can also introduce exclusionary constraints during the candidate order generation process, such as mismatched order statuses between the target email and orders in the order pool, conflicts in business entities, significant conflicts in time windows, inconsistent shipping nodes, and contradictions between attachment content and order details. By combining candidate generation with conflict exclusion, the system can reduce the risk of misassigning emails to similar orders.

[0033] (2.2) Based on the correlation between each target email and its corresponding candidate order, determine the associated order of each target email from the candidate orders.

[0034] Preferably, step (2.2) further includes: (2.1.1) Obtain the first business information of the target email and the second business information of each order in the order pool, and exclude the orders corresponding to the second business information that do not conflict with the first business information from the candidate orders; Step (2.2) further includes: (2.2.1) Based on the correlation between each target email and each first candidate sub-order, the first candidate sub-order that exceeds the preset correlation is determined as the associated order.

[0035] In some embodiments, the determination of associated orders can be based on a comprehensive assessment of the relevance between emails and candidate orders. This assessment can take into account factors such as consistency of business identifiers, consistency of subject relationships, consistency of time relationships, email correspondence, relationship of attachment content, relationship of business stages, continuity of historical communication, and semantic similarity.

[0036] When the system determines that an order and an email have a high degree of correlation (such as exceeding the preset correlation level) and there is no obvious conflict, it automatically establishes a correlation relationship; when the judgment result is uncertain, the email is set to a pending confirmation status and the recommendation basis is shown to the business personnel; when the email may involve multiple orders, it enters the multi-order identification and splitting attribution process; when the email does not match any existing orders, it can output an unrelated or suspected new business lead status.

[0037] Preferably, step (2.2) further includes: (2.2.2) When the associated order of the target email cannot be determined from the candidate orders, output the candidate order that matches the target order or output the suspected new business reminder corresponding to the target order; (2.2.3) When a candidate order for the target email cannot be matched from the order pool, output a suspected new business reminder corresponding to the target order.

[0038] Preferably, step (2.2) further includes: (2.2.4) When the target email has at least two associated orders, the email content of the target email is split into email content fragments, and the associated orders corresponding to each email content fragment are determined.

[0039] In the above implementation, when a target email involves multiple orders, multiple counter numbers, multiple bill of lading numbers, multiple customers, or multiple attachments, the content of the target email is divided according to semantic segments, paragraph structure, attachment table rows, business entity distribution, attachment file names, context topics, or business stages, and different segments are assigned to the corresponding orders.

[0040] During the segmentation process, the source relationship between the fragments and the original emails can be preserved, allowing business personnel to trace back from order communication records to the original email, attachment, paragraph, or table row. This approach avoids simply categorizing entire emails into a single order, thereby reducing the risks of incorrect email archiving, confusion of business records, and difficulties in subsequent retrieval.

[0041] Preferably, the preset dimensions include at least one of the following: business element continuity, business participant relationships, business time, attachment version, and business stage.

[0042] Preferably, step (2) further includes: (2.3) Output the association results of each associated order of each target email; The method further includes the following steps: (5) Obtain feedback results of the association results, and optimize the process of matching each associated order with each target email from the order pool based on the feedback results.

[0043] In some embodiments, the association results can be displayed to business personnel, and their feedback on the order association results (including confirmation, modification, splitting, or merging) can be recorded and used as a basis for subsequent optimization. The feedback results can also be used to update customer contact relationships, business communication habits, order association preferences, stage identification rules, and model performance evaluation.

[0044] This feedback mechanism is not simply a manual review; instead, it feeds back the results of manual confirmation to the subsequent candidate generation, association judgment, and attribution process. This allows the system to gradually adapt to different customers, different business lines, and different email communication habits, thereby improving the stability and usability of subsequent association judgments.

[0045] The apparatus of the present invention for generating records of business email-linked orders, wherein the apparatus includes: A processor is configured to execute computer-executable instructions; The memory stores one or more computer-executable instructions, which, when executed by the processor, implement the various steps of the above-described method for generating records of business email-related orders.

[0046] The present invention discloses a processor for generating records of business email-linked orders, wherein the processor is configured to execute computer-executable instructions, and when the computer-executable instructions are executed by the processor, the various steps of the above-described method for generating records of business email-linked orders are implemented.

[0047] The computer-readable storage medium of the present invention stores a computer program thereon, which can be executed by a processor to implement the various steps of the above-described method for generating records of business email-associated orders.

[0048] In a specific embodiment of the present invention, taking cross-border logistics as an example, a customer sends a batch of export goods information via email. The email subject only states "Please process this batch of goods," and the order number is not explicitly stated in the body of the email, but the attachments include packing lists, invoices, and booking confirmation documents.

[0049] Upon receiving the email, the system parses the body, historical replies, and attachments to identify the customer entity, shipping information, documentation, cargo information, and timeline. It then identifies candidate orders from the order pool and, based on business element consistency, email correspondence, time relationships, order status, and semantic relationships, determines which orders in the candidate pool are highly relevant to the email. Finally, it automatically establishes associations between the email and candidate orders with a higher-than-preset relevance.

[0050] If a single email contains multiple container numbers, multiple bills of lading numbers, or multiple attachment details, the email content is further segmented, and each segment is assigned to its corresponding order. After the association is completed, the system generates a communication record in the order details, including an email summary, to-do items, attachment index, original text location, business stage, and processing status. This confirmation is recorded by the business personnel as a basis for subsequent optimization.

[0051] In another embodiment, the email body does not contain an order number, but the sender belongs to a customer contact, the box number in the attachment matches an in-transit order in the order system, and the sending time falls within the order's data supplementation stage. The system can generate candidate orders and automatically recommend related orders based on the relationships between participants, the content of attachments, and the business stage. If the same customer has multiple similar orders within the same time window, the system can output a pending confirmation status and display the recommendation criteria to avoid erroneous automatic archiving.

[0052] Compared to other methods, this method employs the business email-associated order record generation method of this invention. It can determine the association between emails and existing candidate orders even when there is a lack of explicit order numbers, the title has been repeatedly modified, or business personnel use non-standard expressions. It organizes scattered emails into communication records for orders, transforming emails from communication tools into order fulfillment data, thereby generating communication records of associated orders. Furthermore, it can identify business information related to order fulfillment from unstructured email bodies, historical reply chains, and attachments, and distinguish between current communication content, historical references, and invalid noise content. When an email is identified to involve multiple orders, multiple counter numbers, multiple bills of lading numbers, multiple customers, or multiple business stages, the email content can be broken down and the order to which each email segment belongs can be determined. The results can also be manually confirmed and corrected to continuously optimize subsequent email attribution judgments and adapt to different customers, business lines, and email communication habits.

[0053] For the specific implementation scheme of this embodiment, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0054] It is understood that the same or similar parts in the above embodiments can be referred to each other, and the contents not described in detail in some embodiments can be referred to the same or similar contents in other embodiments.

[0055] It should be noted that in the description of this invention, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Furthermore, in the description of this invention, unless otherwise stated, "a plurality of" means at least two.

[0056] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.

[0057] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution device. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0058] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The corresponding program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0059] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0060] The storage media mentioned above can be read-only memory, disk, or optical disk, etc.

[0061] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0062] Compared to other methods, this method employs the business email-associated order record generation method of this invention. It can determine the association between emails and existing candidate orders even when there is a lack of explicit order numbers, the title has been repeatedly modified, or business personnel use non-standard expressions. It organizes scattered emails into communication records for orders, transforming emails from communication tools into order fulfillment data, thereby generating communication records of associated orders. Furthermore, it can identify business information related to order fulfillment from unstructured email bodies, historical reply chains, and attachments, and distinguish between current communication content, historical references, and invalid noise content. When an email is identified to involve multiple orders, multiple counter numbers, multiple bills of lading numbers, multiple customers, or multiple business stages, the email content can be broken down and the order to which each email segment belongs can be determined. The results can also be manually confirmed and corrected to continuously optimize subsequent email attribution judgments and adapt to different customers, business lines, and email communication habits.

[0063] In this specification, the invention has been described with reference to specific embodiments thereof. However, it will be apparent that various modifications and variations can be made without departing from the spirit and scope of the invention. Therefore, the specification and drawings should be considered illustrative rather than restrictive.

Claims

1. A method for generating records associated with business email orders, characterized in that, The method includes the following steps: (1) In response to the content of each target email, extract the target business event from the content of each target email; The target business events include business information of different business types; (2) Based on the target business event of each target email, match each associated order with each target email from the order pool; (3) Based on each target email and each associated order, determine the set of target emails associated with each associated order; (4) Generate the email history content of the associated orders based on each of the associated orders, the target email set associated with the associated orders, and the preset dimensions; (5) Generate the communication records of the associated order based on the email history content.

2. The method for generating records of business email-linked orders according to claim 1, characterized in that, Step (1) specifically includes: (1.1) In response to the content of each target email, extract at least one business element of each target email from the content of each target email according to the first preset requirement; The business elements include business information for at least one type of business; (1.2) Based on the second preset requirement, at least one business element of the target email is combined into a target business event for each target email.

3. The method for generating records of business email-linked orders according to claim 2, characterized in that, The target email contains the email body and attachments. Step (1.1) specifically includes: (1.1.1) The email body is standardized to obtain the first text; (1.1.2) Extract text from the email attachments based on their type to obtain the second text; (1.1.3) The content of the target email is determined based on the first text and the second text.

4. The method for generating records of business email-linked orders according to claim 1, characterized in that, Step (2) specifically includes: (2.1) Based on the target business event of each target email, match each candidate order corresponding to each target email from the order pool; (2.2) Based on the correlation between each target email and its corresponding candidate order, determine the associated order of each target email from the candidate orders.

5. The method for generating records of business email-linked orders according to claim 4, characterized in that, Step (2.1) further includes: (2.1.1) Obtain the first business information of the target email and the second business information of each order in the order pool, and exclude the orders corresponding to the second business information that do not conflict with the first business information from the candidate orders; Step (2.2) further includes: (2.2.1) Based on the correlation between each target email and each first candidate sub-order, the first candidate sub-order that exceeds the preset correlation is determined as the associated order.

6. The method for generating records of business email-linked orders according to claim 1, characterized in that, Step (2.2) further includes: (2.2.2) When the associated order of the target email cannot be determined from the candidate orders, output the candidate order that matches the target order or output the suspected new business reminder corresponding to the target order; (2.2.3) When a candidate order for the target email cannot be matched from the order pool, output a suspected new business reminder corresponding to the target order.

7. The method for generating records of business email-linked orders according to claim 1, characterized in that, Step (2.2) further includes: (2.2.4) When the target email has at least two associated orders, the email content of the target email is split into email content fragments, and the associated orders corresponding to each email content fragment are determined.

8. The method for generating records of business email-linked orders according to claim 1, characterized in that, The preset dimensions include at least one of the following: business element continuity, business participant relationships, business time, attachment version, and business stage.

9. The method for generating records of business email-linked orders according to claim 1, characterized in that, Step (2) further includes: (2.3) Output the association results of each associated order of each target email; The method further includes the following steps: (5) Obtain feedback results of the association results, and optimize the process of matching each associated order with each target email from the order pool based on the feedback results.

10. An apparatus for generating records of business email-linked orders, characterized in that, The device includes: A processor is configured to execute computer-executable instructions; The memory stores one or more computer-executable instructions, which, when executed by the processor, implement the steps of the method for generating records of business email-associated orders as described in any one of claims 1 to 9.

11. A processor for generating records related to business email orders, characterized in that, The processor is configured to execute computer-executable instructions, which, when executed by the processor, implement the steps of the record generation method for business email-associated orders as described in any one of claims 1 to 11.

12. A computer-readable storage medium, characterized in that, It stores a computer program that can be executed by a processor to implement the various steps of the record generation method for business email-associated orders as described in any one of claims 1 to 9.

Images