Search results
Results from the WOW.Com Content Network
Semantic similarity is a metric defined over a set of documents or terms, where the idea of distance between items is based on the likeness of their meaning or semantic content [citation needed] as opposed to lexicographical similarity. These are mathematical tools used to estimate the strength of the semantic relationship between units of ...
Animation of the topic detection process in a document-word matrix. Every column corresponds to a document, every row to a word. A cell stores the weighting of a word in a document (e.g. by tf-idf), dark cells indicate high weights. LSA groups both documents that contain similar words, as well as words that occur in a similar set of documents.
The space of documents is then scanned using HDBSCAN, [20] and clusters of similar documents are found. Next, the centroid of documents identified in a cluster is considered to be that cluster's topic vector. Finally, top2vec searches the semantic space for word embeddings located near to the topic vector to ascertain the 'meaning' of the topic ...
Distributional semantic models have been applied successfully to the following tasks: finding semantic similarity between words and multi-word expressions; word clustering based on semantic similarity; automatic creation of thesauri and bilingual dictionaries; word sense disambiguation; expanding search requests using synonyms and associations;
Mathematically, this list is an N-dimensional vector of word-document scores, where a document not containing the query word has score zero. To compute the relatedness of two words, one compares the vectors (say u and v) by computing the cosine similarity,
Every column corresponds to a document, every row to a word. A cell stores the frequency of a word in a document, with dark cells indicating high word frequencies. This procedure groups documents, which use similar words, as it groups words occurring in a similar set of documents. Such groups of words are then called topics.
Similarity search is the most general term used for a range of mechanisms which share the principle of searching (typically very large) spaces of objects where the only available comparator is the similarity between any pair of objects. This is becoming increasingly important in an age of large information repositories where the objects ...
Document capacity / Batch processing: Number of documents the system can process per unit of time. [citation needed] Check intensity: How often and for which types of document fragments (paragraphs, sentences, fixed-length word sequences) does the system query external resources, such as search engines. Comparison algorithm type