In one embodiment, a method includes receiving a request to identify k steps for a particular entity to acquire a target attribute in public sentiments, accessing a table of word vector relationships, looking up an entity word vector corresponding to the entity name and a target attribute word vector corresponding to the n-gram representing the target attribute using the table, determining a directional vector in the d-dimensional embedding space that connects from the entity word vector to the target attribute word vector, identifying k points on the directional vector that evenly split the directional vector into k+1 segments, selecting, for each of the k points, a word vector that is closest to the point, identifying, for each of the k selected word vectors, a corresponding n-gram by looking up the word vector in the table, and sending a response message comprising the k identified n-grams.

Provided is a device including: a display unit configured to display handwritten content based on an analog handwritten input of a user; a user input unit that receives a user input of selecting a portion of the handwritten content displayed on the display unit; and a control unit reproduces a segment of multimedia content, which corresponds to the portion of the handwritten content, from the multimedia content synchronized with the handwritten content.

Techniques are provided for performing sentiment analysis on words in a first data set. An example embodiment includes generating a word embedding model including a first plurality of features. A value indicating sentiment for the words in the first data set can be determined using a convolutional neural network (CNN). A second plurality of features are generated based on bigrams identified in the data set. The bigrams can be generated using a co-occurrence graph. The model is updated to include the second plurality of features, and sentiment analysis can be performed on a second data set using the updated model.

The invention relates to a method for recognizing handwriting on a physical surface on the basis of three-dimensional signals originating from sensors of a terminal, the method being characterized in that the signals are obtained on the basis of at least 3 different types of sensors, and in that it comprises steps of sampling, according to 3 axes and over a sliding time window, of inertial signals originating from the sensors, fusing the sampled signals into a 9-dimensional vector for each sampling period, converting the fused signals into a sequence of characteristic 9-dimensional vectors, and, when a signal characteristic of an input start has been detected, storing the sequence of characteristic vectors in a list of sequences of characteristic vectors, the preceding steps being repeated until the detection of a signal characteristic of an input end, the method furthermore comprising, on detection of said signal characteristic of an input end, a step of recognizing a word on the basis of the list of sequences of characteristic vectors created over the time window.

Provided is a device including: a display unit configured to display handwritten content based on an analog handwritten input of a user; a user input unit that receives a user input of selecting a portion of the handwritten content displayed on the display unit; and a control unit reproduces a segment of multimedia content, which corresponds to the portion of the handwritten content, from the multimedia content synchronized with the handwritten content.

A system and method that is able to recognize a user's natural superimposed handwriting without any explicit separation between characters. The system and method is able to process single-stroke and multi-stroke characters. It can also process cursive handwriting. Further, the method and system can determine the boundaries of input words either by the use of a specific user input gesture or by detecting the word boundaries based on language characteristics and properties. The system and method analyzes the handwriting input through the processes of fragmentation, segmentation, character recognition, and language modeling. At least some of these processes occur concurrently through the use of dynamic programming.

Provided is a device including: a display unit configured to display handwritten content based on an analog handwritten input of a user; a user input unit that receives a user input of selecting a portion of the handwritten content displayed on the display unit; and a control unit reproduces a segment of multimedia content, which corresponds to the portion of the handwritten content, from the multimedia content synchronized with the handwritten content.

Process, and related apparatus, that exploits psycho-physiological aspects involved in generation and perception of handwriting for directly inferring from the trace on the paper (or any other means on which the author writes by hand) the interpretation of writing, i.e. the sequence of characters that the trace is intended to represent.

Provided is a device including: a display unit configured to display handwritten content based on an analog handwritten input of a user; a user input unit that receives a user input of selecting a portion of the handwritten content displayed on the display unit; and a control unit reproduces a segment of multimedia content, which corresponds to the portion of the handwritten content, from the multimedia content synchronized with the handwritten content.

Provided is a device including: a display unit configured to display handwritten content based on an analog handwritten input of a user; a user input unit that receives a user input of selecting a portion of the handwritten content displayed on the display unit; and a control unit reproduces a segment of multimedia content, which corresponds to the portion of the handwritten content, from the multimedia content synchronized with the handwritten content.