What is Stemming

1.

The process of removing prefixes and suffixes from words to reduce them to stems thus eliminating tag-of-speech and other verbal or plural inflections. Learn more in: A Primer on Text-Data Analysis

2.

The automatic process of reducing natural language to its most common root form. Learn more in: Amplifying Participant Voices Through Text Mining

3.

Stemming refers to the mapping to word forms to stems or basic word forms. Word forms may differ from stems due to morphological changes necessary for grammatical reasons. Plural for English nouns, for example, is mostly constructed by adding an s to the basic noun. Learn more in: Text Mining

4.

The mapping to word forms to stems or basic word forms. Word forms may differ from stems due to morphological changes necessary for grammatical reasons. Plural for English nouns, for example, is mostly constructed by adding an s to the basic noun. In most European languages stemming needs to strip suffixes of word forms. Learn more in: Information Retrieval

5.

Stemming is the process of reducing word to stem. By removing unnecessary inflammation this is done by removing suffix. Learn more in: Machine Learning in Text Analysis

6.

Stemming refers to the mapping of word forms to stems or basic word forms. Word forms may differ from stems due to morphological changes necessary for grammatical reasons. The plural versions of English nouns, for example, are mostly constructed by adding an s to the basic noun. In most European languages, stemming needs to strip suffixes from word forms. Learn more in: Technologies for Information Access and Knowledge Management

7.

Methods aimed to convert the derived words into the word origin or root. Learn more in: Improving the K-Means Clustering Algorithm Oriented to Big Data Environments

8.

Stemming is the process of reducing a word to its stem or root form. For the purposes of IR, morphological variants of words have similar semantic interpretations and can be considered as equivalent. For example, the word “computation” might be stemmed to “comput”. Stemming is either based on linguistic dictionaries or on algorithms. Learn more in: Towards a Model for Evaluating Web Retrieval Systems in Non-English Queries

9.

Algorithms for reducing a family of words to a common root, or stem, defined as the base form of a word from which inflected forms are derived. Stemming algorithms eliminate all affixes and give good results for the conflation and normalization of uniterm variants. Within this group, the most effective are the longest match algorithms. Learn more in: Standardization of Terms Applying Finite-State Transducers (FST)

10.

The term stemming refers to the reduction of words to their roots so that different grammatical forms or declinations of verbs are identified and indexed as the same word. Learn more in: Corporate Disclosure Measurement

11.

A text normalization technique within the field of Natural Language Processing (NLP) that considers the possible prefixes and suffixes of a specific word to identify other words related to it. For example, the word ‘walk’ which could be linked to ‘walks’, ‘walking’ ‘walker’, etc. Learn more in: Exploring Data Science Initiatives Through an International Lens

12.

In NLP, stemming is the process of reducing words to their word stem, base or root form. For example, if the word is “talking” stemming reduces the word to “talk.” Learn more in: Use of NLP and SEM in Determining Factors for E-Service Adoption

13.

Is the process of reducing inflected forms of a word to its root or stem. Learn more in: Unsupervised Automatic Keyphrases Extraction on Italian Datasets

14.

Stemming is the process of reducing a word to its stem or root form. For the purposes of IR, morphological variants of words have similar semantic interpretations and can be considered as equivalent. For example, the word “computation” might be stemmed to “comput”. Stemming is either based on linguistic dictionaries or on algorithms. Learn more in: Retrieving Non-Latin Information in a Latin Web: The Case of Greek