The phrase "conceptual tags" is correct and can be used in written English.
It refers to labels or categories that represent broad ideas or concepts, rather than specific words or phrases. Example: In online marketing, using relevant conceptual tags can help increase the visibility of your website or blog by making it easier for search engines to understand and categorize your content.
This approach shifts the focus from data processing to concept processing [28], where the tags function as conceptual expressions [29] instead of purely words or phrases.
Hao et al. [79] proposed an approach of variable precision concept [80] based extended conceptual knowledge discovery in folksonomy for tag recommendation and resource suggestion.
The PHIT Data Collaborative conceptual model was reviewed by all TAG members to strengthen its relevance and generalizability.
Several issues have identified including how to recognize terminology in textual document, name concept tags in terminologies, and derive conceptual hierarchies among concepts.
Several experiments clearly showed that during their Internet search, users experienced incongruities between their own conceptual knowledge and that visualized in the tag clouds, which made them internalize the conceptual structure provided by the tag cloud (Cress, Held, & Kimmerle, 2013; Held et al., 2012).
Moreover, the method allowed to incorporate syntagmatic relations among the phenomena to be considered in the representation of word meanings (witness the grammatical tags 'NP'VP'VP' and 'S' attached to the conceptual components above).
The synaptic tagging and capture hypothesis has provided a conceptual framework for how relevant information might be stored in the intervening time period between memory acquisition and memory consolidation and how specific synapses eventually come to store a given memory.
The discussion addresses conceptual, theoretical, and practical issues surrounding the application of harvest tags, as well as challenges and opportunities related to the design of tag programs.
Peptide mass fingerprint data was analyzed against the conceptual translation using PAWS (Digilab, Holliston, MA) and peptide sequence tags derived with Peaks Studio.
Given a sequence of tags (t_{1} t_{2}...t_{n}) where (t_{i}) is a conceptual abstraction of workflow step tag from a Lexicon T, a Motif M in workflows is a small functional unit that occurs significantly more frequently than expected.
