The phrase "aspect extraction" is correct and usable in written English.
It is typically used in contexts related to data analysis, natural language processing, or machine learning, where specific features or components of a dataset are identified and extracted.
Example: "In our study, we focused on aspect extraction to identify key sentiments expressed in customer reviews."
Alternatives: "feature extraction" or "attribute extraction".
Fig. 4 Taxonomy of literature studied for unsupervised aspect extraction.
Multi-level aspect extraction has been a new concept introduced in aspect extraction as agglomerative clustering over the clusters of aspects.
Unsupervised techniques are preferred for aspect extraction because they are efficient and domain independent.
Topic models are preferred for aspect extraction as coherent topics without requiring any manual support.
In this paper, we first examine previous studies on product aspect extraction.
Aspect-based SA was introduced in Hu and Liu (2004) using frequency-relation based technique for unsupervised aspect extraction.
Therefore, we apply two term extraction and two aspects extraction techniques in the set of reviews, and the result of each is evaluated on the recommender system.
In addition, we develop a new aspect-extraction method that combines the results of domain ontology and topic modeling to extract topical features from product descriptions.
We evaluated two aspects, first extraction which was determined in terms of yields and second functionality, which is the ability to identify targets included on the test master list.
Software engineering and software re-engineering rely on such transformations, which are automated in, for example, tools for refactoring, migration, program specialisation, compiler optimisation, database re-engineering, software configuration, business-rule extraction, aspect weaving, aspect mining, architectural modifications, and model-driven approaches.
The best known aspect of supercritical extraction is the possibility to tune the selectivity and solvation capacity.
