公开(公告)号：WO2015009137A1

公开(公告)日：2015-01-22

申请号：PCT/MY2014/000107

申请日：2014-05-09

Applicant: MIMOS BERHAD

Inventor： KHALIL, Ben Mohamad ,  FAROUQ, H. Hamed ,  JASBEER, Singh Atma Singh ,  LIM, Ying Sean ,  DICKSON, Lukose

IPC: G09B7/08

CPC classification number: G09B7/08

Abstract: Method for Collaborative Learning Based on Think-Group-Share Strategy in an Intelligent Collaborative Learning System The present invention provides a method for providing collaborative learning for learners. The method is designed based on a "Think- Group-Share" model where the learners are recommended (202) learning materials (204) and being grouped (210) in a plurality of learning groups. The learners are then being tested (212) with a set of questions and they share (218) answers with the other learners, so that the learners could evaluate (220) the answers. The evaluation results is taken as reference for recommending (228) further learning materials (204). An e-learning platform is also provided herewith.

Abstract translation: 基于智能协同学习系统中的思维组共享策略的协同学习方法本发明提供了一种为学习者提供协作学习的方法。 该方法是基于“Think-Group-Share”模型设计的，其中学习者被推荐（202）学习材料（204）并被分组（210）在多个学习组中。 然后，学习者将通过一系列问题进行测试（212），并与其他学习者共享（218）答案，以便学习者可以评估（220）答案。 评估结果作为推荐（228）进一步学习材料（204）的参考。 此外还提供了一个电子学习平台。

公开(公告)号：WO2014193219A1

公开(公告)日：2014-12-04

申请号：PCT/MY2014/000124

申请日：2014-05-19

Applicant: MIMOS BERHAD

Inventor： KHALIL, Ben Mohamed ,  FAROUQ, H Hamed ,  JASBEER, Singh Atma Singh ,  LIM, Ying Sean ,  DICKSON, Lukose

IPC: G09B7/08

CPC classification number: G09B7/08

Abstract: Method for Collaborative Learning Based on Divide-Master-Lead Strategy in an Intelligent Collaborative Learning System The present invention provides a method for providing collaborative learning for learners. The e-leaming model provides a "divide-master- teach" strategy where the learners are divided (202) in groups where the learners try to master the learning materials as a group. A group leader is selected (212) for each group, and the group of learners will be tested with a set of questions assigned to them. The learners are to evaluating (230, 238, 240) the answers and the interactions between the learners. The evaluation results are utilized for recommending new reading materials and selecting new leaders for the groups. An e-learning platform is also provided herewith.

Abstract translation: 基于智能协同学习系统中的分割主导策略的协同学习方法本发明提供了一种为学习者提供协作学习的方法。 电子挖掘模式提供了一种“师范主导教学”策略，学习者在群体中分组（202），学习者尝试将学习资料作为一组进行掌握。 每个组选择一个组长（212），并且将对一组学习者进行一系列分配给他们的问题的测试。 学习者要评估（230,238,240）答案和学习者之间的交互。 评估结果被用于推荐新的阅读材料，并为群体选择新的领导者。 此外还提供了一个电子学习平台。

公开(公告)号：WO2015080567A1

公开(公告)日：2015-06-04

申请号：PCT/MY2014/000183

申请日：2014-06-13

Applicant: MIMOS BERHAD

Inventor： FAROUQ, H. Hamed ,  BENJAMIN, Chu Min Xian ,  KHALIL, Ben Mohamed ,  DICKSON, Lukose

IPC: G06N5/02

CPC classification number: G06N5/02

Abstract: The present invention relates to a method for converting a knowledge base (110) to binary form. The method includes converting ontology and conceptual structure of a knowledge base (110) to binary form. An ontology translator (121) converts the ontology of a knowledge base (110) to conceptual binary array (CBA) and descendant's binary array (DBA), while a conceptual structure translator (122) converts the conceptual structure of a knowledge base (110) to CBA, relations binary array (RBA) and graph binary array (GBA).

Abstract translation: 本发明涉及将知识库（110）转换为二进制形式的方法。 该方法包括将知识库（110）的本体和概念结构转换为二进制形式。 本体翻译器（121）将知识库（110）的本体转换为概念二进制数组（CBA）和后代的二进制数组（DBA），而概念结构翻译器（122）转换知识库（110）的概念结构， 到CBA，关系二进制数组（RBA）和图二进制数组（GBA）。

公开(公告)号：WO2014092535A1

公开(公告)日：2014-06-19

申请号：PCT/MY2013/000231

申请日：2013-12-05

Applicant: MIMOS BERHAD

Inventor： LIM YING, Sean ,  LEW CHIA, Chyi ,  MANI HAGH, Sefat ,  NOR EZAM, Selan ,  DICKSON, Lukose

IPC: G09B7/12 ,  G09B7/08 ,  G09B5/08

CPC classification number: G09B5/08 ,  G09B7/08 ,  G09B7/12

Abstract: A system (100) for the evaluation of effectiveness of learning content comprising: a learning content repository (101) containing learning content; an assessment repository (102) that contains assessment questions; a learning activity storage module (106) that stores learning activity of a learner (104); a feedback storage module (107) for storing feedback from the learner; a sentiment analysis module (109) adapted to analyse the feedback; an assessment results module (108) adapted to receive assessment results based on the assessment questions and analyse the assessment results; and an evaluation engine (110) adapted to generate an evaluation report on the basis of (i) the learning activity of the learner (104), (ii) sentiment analysis information generated from the feedback of said learner (104), and (iii) assessment result analysis information generated from the assessment results.

Abstract translation: 一种用于评估学习内容的有效性的系统（100），包括：包含学习内容的学习内容存储库（101） 包含评估问题的评估库（102） 学习活动存储模块（106），其存储学习者的学习活动（104）; 用于存储来自学习者的反馈的反馈存储模块（107） 情绪分析模块（109），适用于分析反馈; 评估结果模块（108）适用于根据评估问题接收评估结果并分析评估结果; 以及评估引擎（110），其适于基于（i）学习者的学习活动（104）生成评估报告，（ii）从所述学习者（104）的反馈生成的情绪分析信息，以及（iii） ）评估结果分析信息从评估结果中产生。

公开(公告)号：WO2015060709A1

公开(公告)日：2015-04-30

申请号：PCT/MY2014/000196

申请日：2014-06-26

Applicant: MIMOS BERHAD

Inventor： KHALIL, Ben Mohamed ,  DICKSON, Lukose

IPC: G06N5/02

CPC classification number: G06N5/02

Abstract: The present invention relates to a method for translating a knowledge base. The method comprises the steps of extracting a first semantic network notation (SN1) from a first knowledge base; translating SN1 into a second network notation (SN2) by using a series of SN1 to SN2 translation rules; translating a SN2 into SN1 by using a series of SN2 to SN1 translation rules; storing the translated SN1 in a second knowledge base; and validating the translations.

Abstract translation: 本发明涉及一种用于翻译知识库的方法。 该方法包括从第一知识库中提取第一语义网络符号（SN1）的步骤; 通过使用一系列SN1至SN2转换规则将SN1转换为第二网络符号（SN2）; 通过使用一系列SN2到SN1转换规则将SN2转换为SN1; 将所翻译的SN1存储在第二知识库中; 并验证翻译。

公开(公告)号：WO2014092537A1

公开(公告)日：2014-06-19

申请号：PCT/MY2013/000234

申请日：2013-12-06

Applicant: MIMOS BERHAD

Inventor： JASBEER, Singh Atma Singh ,  FAROUQ, H. Hamed ,  DICKSON, Lukose ,  NOR, Ezam Selan

IPC: G06Q50/00 ,  G06Q10/10

CPC classification number: G06Q50/01 ,  G09B7/02 ,  G09B19/00

Abstract: A system and method for automated generation of learning object from online social content by producing a list of semantic tags through an Entity Recognition System upon matching of concepts 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 Semantic Tag Enrichment Engine (308); at least 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.

Abstract translation: 一种系统和方法，用于通过在域本体中的概念匹配后通过实体识别系统产生语义标签的列表，从在线社交内容自动生成学习对象。 本发明的系统包括多个社会内容（202）; 多个识别引擎，其包括至少一个实体识别引擎（302,414），至少一个语音识别引擎（416），至少一个图像识别引擎（428）; 至少一个语义标签丰富引擎（308）; 至少一个社会内容知识库（206）; 和至少一个学习对象知识库（210）。 所述至少一个实体识别引擎（302,414）具有用于接收与描述，学习目标和学习结果相关联的学习对象的装置; 在领域本体中概念匹配时产生语义标签列表; 以及将所述语义标签列表转发到用于元数据丰富的至少一个语义标签丰富引擎。 简而言之，本发明提供了通过LO浓缩从社会内容中自动生成LO; 社交内容选择和元数据丰富，此后组成完整的LO，包括文字，图像和视频。

公开(公告)号：WO2010110644A2

公开(公告)日：2010-09-30

申请号：PCT/MY2010/000032

申请日：2010-03-22

Applicant: MIMOS BERHAD ,  KOW, Weng, Onn ,  MOHAMMAD, Reza, Beik, Zadeh ,  DICKSON, Lukose

Inventor： KOW, Weng, Onn ,  MOHAMMAD, Reza, Beik, Zadeh ,  DICKSON, Lukose

IPC: G06Q50/00 ,  G06F17/00 ,  G06F9/00

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

Abstract: A method (100) and system (200) for ontology navigation and visualization, the system (200) comprises an ontology navigator (202). The ontology navigator (202) comprises means for graphically displaying a plurality of concepts (102) of at least one ontology knowledge base (206), receiving a user query of at least one concept from the plurality of concepts (104), identifying a visualization application (204) for visualizing the at least one concept (106), generating an information set (108) of the at least one concept recognized by the visualization application (204), and forwarding the information set (110) of the at least one concept to the visualization application (204).

Abstract translation: 用于本体导航和可视化的方法（100）和系统（200），系统（200）包括本体导航器（202）。 本体导航器（202）包括用于以图形方式显示至少一个本体知识库（206）的多个概念（102）的装置，从多个概念（104）接收至少一个概念的用户查询，识别可视化 应用程序（204），其用于可视化所述至少一个概念（106），生成由所述可视化应用程序（204）所识别的所述至少一个概念的信息集合（108），并且将所述至少一个概念 概念到可视化应用程序（204）。

公开(公告)号：WO2015053607A1

公开(公告)日：2015-04-16

申请号：PCT/MY2014/000182

申请日：2014-06-12

Applicant: MIMOS BERHAD

Inventor： ARUN, Anand Sadanandan ,  KOW, Weng Onn ,  CHU MIN XIAN, Benjamin ,  DICKSON, Lukose ,  BAHLS, Daniel

IPC: G06F17/27

CPC classification number: G06F17/2785

Abstract: The present invention relates to a system and method for semantic level sentiment analysis. The system (100) comprises of a graph generator component (10), a semantic sentiment analyser component (20), a sentiment processor component (30), a sentiment dictionary (40), a sentiment taxonomy (50), a semantic sentiment patterns repository (60) and a propagation rules repository (70). The system (100) accepts text data as input and analyses sentiment in the text. The method enables semantically valid sentiment in terms of the entire text as well as the individual entities in the text.

Abstract translation: 本发明涉及语义层面情绪分析的系统和方法。 系统（100）包括图形生成器组件（10），语义情绪分析器组件（20），情感处理器组件（30），情感词典（40），情绪分类（50），语义情绪模式 存储库（60）和传播规则存储库（70）。 系统（100）接受文本数据作为输入并分析文本中的情绪。 该方法在整个文本以及文本中的各个实体方面实现了语义上有效的观点。

公开(公告)号：WO2015047074A1

公开(公告)日：2015-04-02

申请号：PCT/MY2014/000126

申请日：2014-05-28

Applicant: MIMOS BERHAD

Inventor： JASBEER SINGH ATMA, Singh ,  CHU IN XIAN, Benjamin ,  DICKSON, Lukose ,  LIU, Qiang

IPC: G09B7/08

CPC classification number: G09B7/08

Abstract: The present invention relates to a system and method for creating a Learning Object (LO) from a document. Particularly, the system (100) automatically generates the LO at sentence level, paragraph level and topic level in different modalities such as text, image, audio and video. The system (100) comprises a mapper (130), a ranker (140) and a Learning Object Builder (150). The method for creating a Learning Object from a document includes the steps of analysing and processing a document received from a user, matching a retrieved semantic structure by sentence index with a semantic structure from a multimedia repository (120) by the mapper (130), selecting and ranking projected graphs for each type of multimedia by the ranker (140) and producing the Sentence Learning Object, Paragraph Learning Object and Topic Learning Object by the Learning Object Builder (150).

Abstract translation: 本发明涉及一种用于从文档创建学习对象（LO）的系统和方法。 特别地，系统（100）以文本，图像，音频和视频等不同模式自动生成句子级别，段落级别和主题级别的LO。 系统（100）包括映射器（130），游标者（140）和学习对象生成器（150）。 用于从文档创建学习对象的方法包括以下步骤：分析和处理从用户接收的文档，通过语法结构将所检索的语义结构与来自多媒体存储库（120）的语义结构通过映射器（130）匹配， （140）选择和排列每种类型的多媒体的投影图，并由学习对象生成器（150）生成句子学习对象，段落学习对象和主题学习对象。

公开(公告)号：WO2014092546A1

公开(公告)日：2014-06-19

申请号：PCT/MY2013/000251

申请日：2013-12-11

Applicant: MIMOS BERHAD

Inventor： TAN SIEOW, Yeek ,  TAN YEW, Seng ,  DICKSON, Lukose

IPC: G06K9/00

CPC classification number: G06K9/00201 ,  G06K9/00624

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.

Abstract translation: 本发明涉及图像处理系统（100）。 图像处理系统（100）能够计算和分析在图像中检测到的对象之间的空间关系。 图像处理系统（100）包括图像分割和标记组件（110），斑点检测组件（120），空间关系提取器组件（130）和域知识库（140）。 图像处理系统（100）通过执行表面细分计算，二维空间关系计算，三维空间关系计算和空间关系扩展器来提取图像中的对象之间的空间关系。