METHOD AND ARRANGEMENT FOR MONITORING COMPANIES

• US 20160019561A1
• Filed: 09/30/2015
• Published: 01/21/2016
• Est. Priority Date: 03/29/2010
• Status: Active Application

• Current Assignee: Companybook As
• Original Assignee: Companybook As
• Inventors: JELLUM, Harald
• Application Number:
  US14/870,408
• Publication Number:
  US 20160019561A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/0637 Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
• CPC Class Codes: G06Q 10/067 Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 50/00 Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism healthcare informatics G16H
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

Method and arrangement for matching of enterprises and detection of changes for an enterprise by the use of mathematical models that make it possible to match and find similarities between enterprises and also discover changes in an enterprise. The method uses mathematical representation models for enterprises and is suited to make a large number of comparisons automatically. The characteristics of the enterprises are represented by different vectors. The direction and length of the vectors are compared by taking the scalar product between them. Changes for the characteristics of an enterprise appear as changes in the direction and length of the vectors. By continuously monitoring the derivative of the characteristics of the enterprises this show how large and how quickly a change has occurred. The market for the invention is local and global enterprises that wish to find new customers, partners, distributors or other business contacts and also discover changes for in their customers, partners or other business contacts so that they can get an early warning of larger changes that will have consequences for the relationship.

Claims

1. A method for comparing enterprises and detection of changes in an enterprise comprising server means adapted to use mathematical models that make it possible to match and find similarities between enterprises and also to discover changes in an enterprise and a database for storing the characteristics of the enterprises,

the method comprising the following steps:

a) a combination of information about an enterprise collected by search engine technology and where the characteristics of the enterprise are represented with the help of vector mathematics;

b) wherein the search engine continuously reads the web pages of the enterprises, public enterprise registers, financial registers, news, forums, blogs, social networks and feedback from the user;

c) wherein the information is categorised as characteristics within location, sector, market, product, services, organisation, finance or other relevant categories;

d) and which are converted into mathematical vectors that represent the characteristics of the enterprise, the vectors being stored in the database; and

e) wherein the enterprises are compared by comparing the scalar product between the characteristic vectors of the enterprise.

2. The method according to claim 1, wherein changes in the characteristics of an enterprise are expressed as changes in a characteristic vector with speed, length and direction.

3. The method according to claim 1, wherein a characteristic of an enterprise is represented as a vector in a multi-dimensional room where each direction represents a unique word (part characteristic).

4. The method according to claim 3, wherein the characteristic vector of an enterprise comprises the sum of each part characteristic which encompasses vectors represented by one or more unique words or compositions.

5. The method according to claim 4, wherein a part characteristic vector has a length which is inversely proportional to the appearance of all the words given by an adaptive wordlist and proportional to the appearance, location, size or meaning within an enterprise.

6. The method according to claim 1, wherein a comparison between one or more enterprises is made by the scalar product which is converted to a readable value between 0-100%.

7. The method according to claim 1, wherein a change in an enterprise is represented as changes in direction and length of a characteristic vector of an enterprise that is created by regarding the derivative of a vector.

8. The method according to claim 1, wherein the characteristic of an enterprise is represented as a vector with a normalised length by storing in a database and that the length itself is calculated dynamically at the time of the comparison, to the whole time reflect the adaptive wordlist which all the time is updated by crawling of the information sources.

9. The method according to claim 1, wherein an enterprise vector can comprise one or more of the characteristic vectors of an enterprise.

10. The method according to claim 1, wherein an enterprise can overrule the length of a vector which is given by the adaptive wordlist due to other priorities that are important for the enterprise such as campaigns, strategy changes, visibility or other business reasons.

11. The method according to claim 1, wherein an enterprise matching can combine vector comparison with several other parameters such as regulations, external influences, strategies or other wishes that are important for the enterprise or its environment.

12. The method according to claim 1, wherein changes in an enterprise vector can lead to an early warning which is sent as a message to the users.

13. The method according to claim 1, wherein the vectors of enterprise that have relatively the same direction and length can automatically form groups with enterprises that have many features in common.

14. The method according to claim 1, wherein changes in the vectors of an enterprise can detect market trends and market changes.

15. The method according to claim 1, wherein changes in the vectors of enterprises can detect positive or negative directions for an enterprise.

16. The method according to claim 1, wherein changes in the vectors of enterprises can detect new customers, partners, competitors or other business contacts.

17. The method according to claim 1, wherein changes in the vectors of enterprises can detect new markets based on trends within the changes in the market and products of other enterprises.

18. The method according to claim 1, wherein the vectors of enterprises based on information from forums, blogs, social networks, news or users can provide a live indication of the product, services and brand status of an enterprise and its development in positive or negative directions by comparing with defined positive and negative vectors.

19. A system for matching of enterprises and detection of changes for an enterprise with the use of mathematical models that make it possible to match and find similarities between enterprises and also discover changes in an enterprise, the system comprising:

a) a search engine connected to a network set up for collecting enterprise information;

b) wherein the search engine is set up to essentially continuously read the web pages of enterprises, public enterprise registers, financial registers, news, forums, blogs, social networks and feedback from the users;

c) a categorising unit set up to categorise the information collected by the search engine within location, sector, market, product, services, organisation, financial or other relevant categories;

d) a calculation unit set up to make the categorised information to mathematical vectors that represent the characteristics of an enterprise; and

e) a comparing unit for comparing the enterprises stored in the memory by taking the scalar product (76) between the characteristic vectors of the enterprise.

20. The system according to claim 19, wherein changes in the characteristics of an enterprise are expressed as changes in characteristic vectors with speed, length and direction.