公开(公告)号：US20160189037A1

公开(公告)日：2016-06-30

申请号：US14582235

申请日：2014-12-24

Applicant: Intel Corporation

Inventor： Oren Pereg ,  Moshe Wasserblat ,  Michel Assayag ,  Alexander Sivak ,  Saurav Sahay ,  Junaith Ahemed Shahabdeen

IPC: G06N5/04 ,  G06N7/00 ,  G06N99/00

CPC classification number: G06N5/04 ,  G06N7/005 ,  G06N20/00

Abstract: One embodiment provides an apparatus. The apparatus includes a processor; at least one peripheral device coupled to the processor; a memory coupled to the processor; a generic sentiment model and a first domain training corpus stored in memory; and a hybrid sentiment analyzer logic stored in memory and to execute on the processor. The hybrid sentiment analyzer logic includes a sentiment lexicon generator logic to generate a domain sentiment lexicon based, at least in part, on the first domain training corpus and to store the domain sentiment lexicon in memory, a lexicon-based sentiment classifier logic to generate an annotated training corpus unsupervisedly, based, at least in part, on the domain sentiment lexicon and to store the annotated training corpus in memory, and a model-based sentiment adaptor logic to adapt the generic sentiment model based, at least in part, on the annotated training corpus to generate an adapted sentiment model and to store the adapted sentiment model in memory.

Abstract translation: 一个实施例提供了一种装置。 该装置包括处理器; 耦合到所述处理器的至少一个外围设备; 耦合到所述处理器的存储器; 通用情绪模型和存储在记忆体中的第一域训练语料库; 以及存储在存储器中并在处理器上执行的混合情绪分析器逻辑。 混合情绪分析器逻辑包括情感词典生成器逻辑，用于至少部分地基于第一域训练语料库生成域信息词典，并将域信息词典存储在存储器中，基于词典的情绪分类器逻辑，以生成 至少部分地基于领域情绪词典并且将注释的训练语料库存储在记忆体中，以及基于模型的情绪适配器逻辑，以至少部分地基于模型的情感适配器逻辑来适应通用情绪模型， 注释的训练语料库以产生适应的情绪模型并将适应的情绪模型存储在存储器中。

公开(公告)号：US10380256B2

公开(公告)日：2019-08-13

申请号：US14866889

申请日：2015-09-26

Applicant: Intel Corporation

Inventor： Lama Nachman ,  Ashwini Asokan ,  Giuseppe Raffa ,  Rita H. Wouhaybi ,  Saurav Sahay ,  Omar U. Florez ,  Rahul C. Shah ,  Chieh-Yih Wan ,  Jonathan J. Huang ,  Hong Lu ,  Sangita Sharma ,  Junaith Ahemed Shahabdeen ,  Douglas P. Bogia ,  Lenitra Durham

IPC: G06F17/27 ,  G06N5/02 ,  G06F16/9535

Abstract: Technologies for automated context-aware media curation include a computing device that captures context data associated with media objects. The context data may include location data, proximity data, behavior data of the user, and social activity data. The computing device generates inferred context data using one or more cognitive or machine learning algorithms. The inferred context data may include semantic time or location data, activity data, or sentiment data. The computing device updates a user context model and an expanded media object graph based on the context data and the inferred context data. The computing device selects one or more target media objects using the user context model and the expanded media object graph. The computing device may present context-aware media experiences to the user with the target media objects. Context-aware media experiences may include contextual semantic search and contextual media browsing. Other embodiments are described and claimed.