公开(公告)号：EP2411956A4

公开(公告)日：2013-02-27

申请号：EP10756391

申请日：2010-03-22

Applicant: MIMOS BERHAD

Inventor： KOW WENG ONN ,  MOHAMMAD REZA BEIK ZADEH ,  DICKSON LUKOSE

IPC: G06Q50/00 ,  G06F3/048 ,  G06F3/0482 ,  G06F9/00 ,  G06F17/00

CPC classification number: G06F17/30554 ,  G06F3/0482 ,  G06F17/30994

公开(公告)号：MY185354A

公开(公告)日：2021-05-09

申请号：MYPI2013004281

申请日：2013-11-27

Applicant: MIMOS BERHAD

Inventor： BENJAMIN CHU MIN XIAN ,  DANIEL BAHLS ,  DICKSON LUKOSE

Abstract: The present invention provides a system for extracting concept and named-entities from a text-containing document. An entity recognition engine (102) is provided to process an entity with a Rule-based Named-Entity Recognition (NER) (122), a Natural-Language-Processing (NLP) based NER (124), and a knowledge-based NER (126). The NERs are further scored and weighted, wherein the highest weighted score will be taken. A method thereof is also provided. (Figure 1)

公开(公告)号：MY164485A

公开(公告)日：2017-12-29

申请号：MYPI20093029

申请日：2009-07-20

Applicant: MIMOS BERHAD

Inventor： NAVNIT SINGH BIRING ,  MOHAMMAD REZA BEIK ZADEH ,  DICKSON LUKOSE

IPC: G06F15/16 ,  G06F21/00 ,  G06Q40/00

Abstract: A METHOD (100) AND SYSTEM (200) FOR AN INTELLIGENT FRAMEWORK FOR SERVICE ORIENTATED ARCHITECTURE (202), WHEREIN THE SYSTEM COMPRISES A PLURALITY OF LOOKUP SERVICES (204), A PLURALITY OF DELEGATOR SERVICES (206) AND AT LEAST ONE AUTHENTICATOR SERVICE (208). THE PLURALITY OF LOOKUP SERVICES (204) COMPRISES MEANS FOR MAINTAINING A REGISTRATION OF A PLURALITY OF SERVICES OF THE SERVICE ORIENTATED ARCHITECTURE (102), STORING A SERVICE LOCATION OF EACH OF THE PLURALITY OF SERVICES (104), ITERATING WITHIN A CONFIGURABLE INTERVAL, A VALIDITY INSPECTION OF THE SERVICE LOCATION OF EACH OF THE PLURALITY OF SERVICES (106), IDENTIFYING THE SERVICE LOCATION OF AN INITIAL SERVICE FROM THE PLURALITY OF SERVICES REQUIRED TO PROCESS A CLIENT REQUEST (108) AND STORING A SERVICE STATUS OF EACH OF THE PLURALITY OF SERVICES (110). THE PLURALITY OF DELEGATOR SERVICES (206) COMPRISES MEANS FOR RECEIVING THE CLIENT REQUEST, DELEGATING THE CLIENT REQUEST TO THE INITIAL SERVICE (114) FOR PROCESSING THE CLIENT REQUEST TO GENERATE A RESPONSE (116) AND FORWARDING THE RESPONSE TO THE CLIENT (118). THE AT LEAST ONE AUTHENTICATOR SERVICE (208) COMPRISES MEANS FOR AUTHENTICATING THE CLIENT. THE MOST ILLUSTRATIVE DRAWINGS: FIGS. 1 & 2

公开(公告)号：MY164083A

公开(公告)日：2017-11-30

申请号：MYPI2012004796

申请日：2012-11-01

Applicant: MIMOS BERHAD

Inventor： KOW WENG ONN ,  ARUN ANAND SADANANDAN ,  DICKSON LUKOSE

IPC: G06F17/30

Abstract: A SYSTEM (100) FOR DISTRIBUTED QUERYING OF LINKED SEMANTIC WEBS (110) COMPRISING AT LEAST ONE LOD ONTOLOGIES INDEX (120) COMPRISING LOD ONTOLOGIES AND METADATA RELATING TO SAID LOD ONTOLOGIES; AT LEAST ONE CONCEPT INDEX (130) COMPRISING CONCEPTS AND CORRESPONDING URIs; AT LEAST ONE RELATION INDEX (140) COMPRISING RELATIONS AND CORRESPONDING URIs; QUERY INTERFACE (160) FOR ENTERING SPARQL QUERIES; AND A DISTRIBUTED QUERY ENGINE (150) IN COMMUNICATION WITH SAID LOD ONTOLOGIES INDEX (120), CONCEPT INDEX (130) AND RELATIONS INDEX (140) AND ADAPTED TO RECEIVE QUERIES FROM SAID QUERY INTERFACE (160); CHARACTERISED IN THAT SAID DISTRIBUTED QUERY ENGINE (150) IS ADAPTED TO: PARSE AND REWRITE QUERIES RECEIVED FROM SAID QUERY INTERFACE (160) AND GENERATE A PLURALITY OF SUB-QUERIES; IDENTIFY DEPENDENCIES WITHIN SAID SUB-QUERIES AND CHUNK SUB-QUERIES BASED ON ONTOLOGY; EXECUTE SUB-QUERIES BY SENDING TO RELEVANT SOURCE ONTOLOGY; AND MERGE RESULTS OBTAINED FROM EXECUTION OF SAID SUB-QUERIES. THE MOST ILLUSTRATIVE DRAWING IS

公开(公告)号：MY158357A

公开(公告)日：2016-09-30

申请号：MYPI2012005373

申请日：2012-12-12

Applicant: MIMOS BERHAD

Inventor： JASBEER SINGH ATMA SINGH ,  FAROUQ H HAMED ,  DICKSON LUKOSE ,  NOR EZAM SELAN

Abstract: A SYSTEM AND METHOD FOR AUTOMATED GENERATION OF LEARNING OBJECT SOCIAL CONTENT BY PRODUCING A LIST OF SEMANTIC TAGS THROUGH AN ENTITY RECOGNITION IN DOMAIN ONTOLOGY. THE SYSTEM OF THE PRESENT INVENTION INCLUDES A PLURALITY OF SOCIAL CONTENTS (202); A PLURALITY OF RECOGNITION ENGINES WHICH INCLUDES AT LEAST ONE ENTITY RECOGNITION ENGINE (302, 414), AT LEAST ONE SPEECH RECOGNITION ENGINE (416), AT LEAST ONE IMAGE RECOGNITION ENGINE (428); AT LEAST ONE SEMATIC TAG ENRICHMENT ENGINE (308); AT LEAST IMAGE ONE SOCIAL CONTENT KNOWLEDGE BASE (206); AND AT LEAST ONE LEARNING OBJECT KNOWLEDGE BASE (210). THE AT LEAST ONE ENTITY RECOGNITION ENGINE (302, 414). HAVING MEANS FOR RECEIVING LEARNING OBJECT THAT IS ASSOCIATED WITH DESCRIPTION, LEARNING OBJECTIVE AND LEARNING OUTCOME; PRODUCING A LIST OF SEMANTIC TAGS UPON MATCHING OF CONCEPTS IN DOMAIN ONTOLOGY; AND FORWARDING SAID LIST OF SEMANTIC TAGS TO AT LEAST ONE SEMANTIC TAG ENRICHMENT ENGINE FOR METADATA ENRICHMENT. IN SHORT, THE PRESENT INVENTION PROVIDES FOR AUTOMATED GENERATION OF LO FROM SOCIAL CONTENTS THROUGH LO ENRICHMENT; SOCIAL CONTENT SELECTION AND METADATA ENRICHMENT AND THEREAFTER COMPOSING COMPLETE LO WHICH INCLUDES TEXT, IMAGE AND VIDEO.

公开(公告)号：MY188277A

公开(公告)日：2021-11-25

申请号：MYPI2015704001

申请日：2015-11-05

Applicant: MIMOS BERHAD

Inventor： BENJAMIN CHU MIN XIAN ,  KHALIL BOUZEKRI ,  SHAZZAT HOSSAIN ,  TARIQUE AZIZ ,  DICKSON LUKOSE

IPC: G06F17/00

Abstract: The present invention relates to a system (100) and method for matching two or more documents. The system (100) for semantic matching of documents comprising a semantic parser (10) configured to parse the document to identify simple and complex attributes, a semantic matcher (30) configured to identify a plurality of candidate documents, filter out the candidates documents, and compute semantic similarity of documents using various semantic relationships between attributes, and a data sources manager (40) configured to manage input data sources from a data repository. The system (100) further comprising a hidden semantic knowledge extractor (20) configured to extract hidden semantic relationship between attributes and to create a discovered knowledge graph (56) from the hidden semantic relationship between attributes.

公开(公告)号：MY188005A

公开(公告)日：2021-11-09

申请号：MYPI2012005159

申请日：2012-11-29

Applicant: MIMOS BERHAD

Inventor： ARUN ANAND SADANANDAN ,  TAN SIEOW YEEK ,  DICKSON LUKOSE

Abstract: A system and method (100, 200) for automated generation of contextual knowledge-base by utilizing contextual revised knowledge-base generator (102), the said contextual knowledge-base generator (102) comprising at least one Salient Entity List Composer module (204); at least one Concept Extension module (208); at least one Ontology Content Mapping module (212); and at least one Revised Knowledge-base Reconstruction module (214). The at least one Revised Knowledge-base Reconstruction module (214) having means for receiving domain knowledge base with concepts from mapped content ontology; determining if said concepts are marked and further processing marked concepts by preserving original hierarchy structure of marked concepts; preserving instances attached to marked concepts; preserving properties with its domain as preserved instances; and removing unmarked concepts from ontology while preserving original hierarchy structure of said marked concepts. In short, the invention automatically identify all concepts, properties and instances (C,P,I) for a revised knowledge-base from a domain knowledge-base based on specific entities and associated contextual information.

公开(公告)号：MY182742A

公开(公告)日：2021-02-04

申请号：MYUI2014703501

申请日：2014-11-25

Applicant: MIMOS BERHAD

Inventor： KHALIL BOUZEKRI ,  JASBEER SINGH A/L ATMA SINGH ,  FAROUQ HATEM HAMAD ,  DICKSON LUKOSE

Abstract: The present invention relates to a system for providing a learning plan (100). The system (100) is characterised by a Student Model repository (110) to store students? details, a Question Bank repository (120) to store questions, a Cluster Data Storage repository (130) to store students? cluster profile, a Learning Material repository (140) to store learning materials, an Assessment Based Learning Planner module (150) to assess and assign students with knowledge states and learning plans, a Cluster Based Learning Planner module (160) to create student profile clustering, a Personalized Learning Plan Selector module (170) to present students with learning materials based on the matched knowledge states and learning plans, a Knowledge Space Theory Library (180) to store functions for Knowledge Structure building and a Psych Library (190) to store functions and criteria for cluster profiling.

公开(公告)号：MY181677A

公开(公告)日：2020-12-31

申请号：MYPI2014701129

申请日：2014-05-05

Applicant: MIMOS BERHAD

Inventor： BENJAMIN CHU MIN XIAN ,  SIMON LIU QIANG ,  DICKSON LUKOSE

Abstract: The present invention relates to a system (1000) and method for generating knowledge base (111) automatically from structured and unstructured texts. The system (1000) which generates a knowledge base (111) automatically from natural language texts, comprises of a Knowledge Base Generator (100) which utilises a Linked Data (LD) (108); a Linguistic Resource (LR) (109); and an Extraction Patterns component (110) to support a series of process and techniques for the Knowledge Base Generator (100). The Knowledge Base Generator (100) further comprises a Concept Pruning component (101), a Concept Taxonomy Derivation component (102), a Property Taxonomy Derivation component (103), an Individuals Identification component (104), a Generic Relation Extraction component (105), a Semantic Relation Discovery component (106) and a Resolution component (107). FIG. 1

公开(公告)号：MY181673A

公开(公告)日：2020-12-31

申请号：MYPI2012701161

申请日：2012-12-13

Applicant: MIMOS BERHAD

Inventor： TAN YEW SENG ,  TAN SIEOW YEEK ,  DICKSON LUKOSE

IPC: G06K9/00

Abstract: The present invention relates to an image processing system (100). The image processing system (100) is able to compute and analyse spatial relationship between objects detected in an image. The image processing system (100) comprises of an image segmentation and labelling component (110), a blob detection component (120), a spatial relationship extractor component (130), and a domain knowledge base (140). The image processing system (100) extracts spatial relationship between objects in an image by performing a surface subdivision computation, two-dimensional spatial relation computation, three-dimensional spatial relation computation and spatial relation extender. (Figure 1)