Conversations and agents persist on disk, so you can develop an agent, restart it, and continue without losing state. Conversations can also be downloaded, making it easy to share demos and test results. Additionally, agents can be cloned to work with different configurations, allowing for pa...
Then, the pixels are transformed into La*b* color space creating a distribution which is the input to a Conditional Random Field (CRF) model, thus providing unary features. Last, pair-wise depth-based featured are formed by taking into consideration the vertical alignment, the depth difference...
We began anInnovations Contestin the field of Neuro-Semantics in 2012. Because we have so many very creative people in this field — and because we want to avoid the lack of support for Innovation in the field of NLP — the leadership team decided in 2011 that we would run a contest an...
uidNoStringThe unique ID of the user (not the developer). This is used to distinguish between users in the app (we recommend using the user's openid). If this field is left blank, you cannot use the context understanding feature, because this requires both the AppID and UID. ...
Lecturer:Prof.Dr.CHENYanEmail:cyan@xmu.edu.cn Majorcontents 9.1Hyponymy(下义关系)9.2Taxonomy(分类关系)9.3Partonomy(部分整体关系)9.4Semanticfield(语义场) hyponymyRelationshipofinclusion 下义关系 taxonymypartonymy 分类关系 部分整体关系 Hyponymy:Definition Hyponymy[haɪ'pɒnɪm...
SWT exploitation in the IoT field provides an explicit, easy and comprehensible description in order to express semantic objects and their data. In addition, semantics subscribes to define consensus that facilitates dataset sharing, reuse, integration, and interrogation. This data, extracted from ...
Field agents ideally need to see enough visual real-time, mapped airspace information on the sensor activated, allowing them to move quickly and directly to the location. Specifics are important; verbally relayed information by contrast can often be less specific, causing confusion or misunderstanding...
Simplicity: Easy setup process without the need for deep machine learning knowledge. Cost-Effectiveness: Eliminates cloud costs, making it wallet-friendly. Privacy: Ensures data processing happens on your local machine, enhancing user privacy.
Text analysis is a major area of research in this field, where semantic information is derived from purely textual input data. In recent years, text analysis approaches have made significant progress and are successfully deployed in a wide range of real-world applications [3, 17, 33]. Textual...
Likert scales with ratings ranging from 1 to 5. Furthermore, the evaluation methodology adopted to scrutinize the critical features of OntoBuilder is delineated in detail. The evaluation was performed with the participation of 10 users, all of whom are researchers in the field of computer science...