Method and apparatus for trade interaction chain reconstruction

1. A method for trade interaction chain reconstruction, comprising:

receiving audio interactions and text interactions by a computerized system executed on one or more general purpose computers;

pre-processing the interactions by extracting words from the audio interactions and metadata from the audio interactions and the text interactions; wherein the metadata includes an order ID, an execution ID or a swap deal ID;

storing the pre-processed interactions and results of the pre-processing in a storage device;

querying the storage device with an expression to identify a swap deal, the swap deal includes two or more of the received interactions and involves two or more participants;

assigning a relevance score of each interaction to the query expression;

sorting the interactions by the relevance score;

automatically selecting from the storage device based on the relevance score a first interaction of the received interactions, said first interaction involves at least two participants of the two or more participants;

obtaining a first plurality of interactions of the received interactions that involve the at least two participants of the two or more participants;

filtering the obtained first plurality of interactions based on metadata parameters;

determining a first plurality of relevance scores between the first plurality of interactions and the first interaction; and associating interactions of the first plurality of interactions to be relevant to the swap deal according to the determined first plurality of relevance scores

outputting to a chain storage module a potential list of interactions that were determined to be relevant to the swap deal;

wherein the preprocessing comprises:

automatically transcribing the received audio interactions;

extracting words, phrases and named entities from the received interactions;

associating metadata to the receive interactions;

categorizing the received interaction into categories;

wherein the named entities include names of people, names of organizations or names of locations; and

wherein the categories are identified by assigning a category score that is a function of a log of one plus the inverse of the sum of the number of extracted words, extracted named entities and extracted metadata or a specific interaction.

2. The method according to claim 1 , wherein the received interactions are textual interactions.

3. The method according to claim 1 , wherein the received interactions are audio interactions.

4. The method according to claim 1 , wherein the first plurality of interactions that involve the at least two participants are obtained according to a predetermined set or rules.

5. The method according to claim 1 , further comprises ranking the first plurality of interactions according to the first plurality of relevance scores.

6. The method according to claim 5 , wherein the first plurality of relevance scores are determined based on a first similarity measure function between the first interaction and the first plurality of interactions.

7. The method according to claim 6 , wherein the first similarity measure function is based on parameters selected from a group consisting of word frequencies, phrase frequencies, named entities, category scores and associated metadata.

8. The method according to claim 5 , further comprises selecting a first portion of interactions of the first plurality of interactions according to the first plurality of relevance scores.

9. The method according to claim 1 , further comprises obtaining a second plurality of interactions from the received interactions that involve at least one participant of the two or more participants of the swap deal.

10. The method according to claim 9 , further comprises ranking the second plurality of interactions according to a second plurality of relevance scores.

11. The method according to claim 10 , wherein the second plurality of relevance scores are determined based on a second similarity measure function between the first portion of interactions of the first plurality of interactions and the second plurality of interactions.

12. The method according to claim 11 , wherein the second similarity measure function is based on parameters selected from a group consisting of word frequencies, phrase frequencies, named entities, category scores and associated metadata.

13. The method according to claim 1 , further comprises selecting a second portion of interactions of a second plurality of interactions.

14. The method according to claim 13 , wherein the second portion of interactions is selected according to a second plurality of relevance scores.

15. The method according to claim 14 , further comprises generating the list of potential swap deal interactions by combining the first portion of interactions and the second portion of interactions.

16. The method according to claim 15 , further comprises displaying the list of potential swap deal interactions sorted by the first plurality of relevance scores and the second plurality of relevance scores.

17. The method according to claim 16 , further comprises enabling playback of audio interactions and enabling display of textual interactions on the list of potential swap deal interactions.

18. The method according to claim 16 , further comprises enabling a user to verify the relevance of the displayed interactions to the swap deal.

19. The me according to claim 18 , further comprises displaying the verified interactions in a timely manner.

20. The method according to claim 1 , wherein the filtering removes interactions that are captured more than a specific number of days after the capturing date of the interaction or prior to the interaction.

21. The method according to claim 1 , further comprising displaying the potential list of interactions that were determined to be relevant to the swap deal and enabling a user to associate or disassociate any interaction of the list with the swap deal.