Yes, you are right. Currently available methods do not provide proper framework. Please understand that knowledge is not made of one structure. We strongly believe that a combination will provide some clue.

We have worked substantially on this area. We used various (2-3) knowledge representation methods to build up a more manageable network for better knowledge storage, representation and retrieval. Poonam Tanwar, my research scholar, had done extensive work. Combining all methods will also be quite cumbersome at initial level. It may lead to a life long research activity. We chose to take few techniques and integrate them.

Have a nice time and use best of innovation...

Dr. T. V. Prasad

Would you suggest that I read your paper: Hybrid technique for effective knowledge representation & a comparative study Poonam Tanwar, T. V. Prasad, Kamlesh Datta? If there are others that you believe would be useful for me please let me know.

This is exactly what I would like to build, but I am approaching it from an Industrial Design point of view.

We have been working on a MultiLayer graph based Next Generation personal knowledge organization tool anchored in WikiData and knowledge engine WikiNizer rebranded as MindGraph.

The multiplicity of layers comes from the fact that the edges are elaborated in a next level up meta-graph ( it is turtles all the way up as needed).

Thanks to the internet archive the original announcement have been saved at https://web.archive.org/web/20180208164825/https://linkedup-project.eu/2014/12/22/wikinizer-introducing-mindgraph/ https://www.linkedin.com/in/gyuri-lajos/

Hi, maybe multiplex lexical networks might be of relevance here.

Together with my co-authors, we built a multiplex network representation of word-word similarities including different layers/aspects of language such as synonyms/feature sharing/free associations/taxonomical relationships and also other phonological aspects.

In children we found that the multiplex structure has a higher prediction power compared to single layer networks or to other psycholinguistic variables (e.g. frequency, length) in predicting normative age of acquisition, how most English toddlers learn words over time.

https://www.nature.com/articles/srep46730

In adults we found that the multiplex layers allow to detect a core of densely connected concepts which: (i) emerges suddenly through an explosive phase transition around age 7-8 yrs and (ii) makes the whole mental lexicon highly resilient to random word failures (e.g. concepts becoming progressively inaccessible).

https://www.nature.com/articles/s41598-018-20730-5

In clinical populations like people with aphasia, we also found that the multiplex closeness of words is an important predictor of performance in a picture naming task (when shown a picture, can people with aphasia name the concept represented in the picture?). This predictive power is absent on the individual layers composing the multiplex lexical network but it appears when multiple semantic and phonological layers are combined together.

https://psyarxiv.com/eqvmg/

Hope these works can be of relevance for your research!