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In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis.Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1]
The transactional net margin method (TNMM) in transfer pricing compares the net profit margin of a taxpayer arising from a non-arm's length transaction with the net profit margins realized by arm's length parties from similar transactions; and examines the net profit margin relative to an appropriate base such as costs, sales or assets.
Pricing designed to have a positive psychological impact. For example, there are often benefits to selling a product at $3.95 or $3.99, rather than $4.00. If the price of a product is $100 and the company prices it at $99, then it is using the psychological technique of just-below pricing.
The negative sampling method, on the other hand, approaches the maximization problem by minimizing the log-likelihood of sampled negative instances. According to the authors, hierarchical softmax works better for infrequent words while negative sampling works better for frequent words and better with low dimensional vectors. [3]
In practice however, BERT's sentence embedding with the [CLS] token achieves poor performance, often worse than simply averaging non-contextual word embeddings. SBERT later achieved superior sentence embedding performance [8] by fine tuning BERT's [CLS] token embeddings through the usage of a siamese neural network architecture on the SNLI dataset.
The bag-of-words model (BoW) is a model of text which uses an unordered collection (a "bag") of words. It is used in natural language processing and information retrieval (IR). It disregards word order (and thus most of syntax or grammar) but captures multiplicity .
Cost-plus pricing is the most basic method of pricing. A store will simply charge consumers the cost required to produce a product plus a predetermined amount of profit. Cost-plus pricing is simple to execute, but it only considers internal information when setting the price and does not factor in external influencers like market reactions, the weather, or changes in consumer va
T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [ 1 ] [ 2 ] Like the original Transformer model, [ 3 ] T5 models are encoder-decoder Transformers , where the encoder processes the input text, and the decoder generates the output text.