Review Comment:
I would like to thank the authors for taking the reviewers' comments into account and considerably improving the readability of the paper. While I still believe that the level of innovation is somewhat limited, the paper provides interesting results by offering a very profound evaluation of the influence of combining similarity-based and different filtering options with knowledge-graph queries.
The overall functioning of the system has become much clearer with the restructuring, however, the difference in numbering steps between the description on page 4 and the visualization on page 5 in Fig.1 are still somewhat confusing. There are only 10 steps in the description, but 12 in the graph. Furthermore, there seems to be no single connection to the optimizer and also step 5 in the description is rather unclear. Maybe you could improve on this part a bit more.
To make the contributions even more clear, the abstract and introduction should really talk more about query language and search strategies than system. For if this is really a system, it is entirely unclear to me on which basis the system decides when to switch between different types of queries and filtering steps.
There are also still some expressions that are not intuitive and also not explained in the paper. For instance, what is a "rollup" query pattern? The same goes for the sentence where it first occurs with "three rollup patterns" - which three patterns? Another example is the "maximum frequency among relevant resources" => frequency of what? It would also be nice to provide a succinct "these are the most important findings" of the paper at the end. The only reason this is not provided I presume is because the authors for some reason decided to omit the very much standard section "Conclusion". I strongly recommend adding both, a succinct summary in two sentences and a Conclusion.
In the Results sections the authors start by indicating a percentage of participants without ever stating the number of participants. This is absolutely necessary in order to understand this section. Only providing it in a table later on is not sufficient for such an important piece of information.
In terms of formatting, the paper needs some attention. "Table" should never be abbreviated as "Tab" or "Tabs" whereas Figure usually is abbreviated as "Fig." in the running text. When an author name is provided, such as Adomavicius et al. this needs to be followed by the reference such as "Adomavicius et al. [2]" instead of adding the reference to the end of the next sentence. This occurs several times in the paper. The reference of footnote 1 to the general resource of DBpedia has absolutely no relation to the content of the sentence where it is placed in the text. And for abbreviations, please use "Information Retrieval (IR)" somewhere before using the abbreviation. Definition 12 and 13 are identical to Definitions 6 and 7 - only the input is different. I suggest omitting those two definitions and instead stating that the IC is then calculated the same as before. As it is now, it is incorrect, since Definition 12 states "Conditional SKOS similarity" - but the similarity is not conditional and in fact the same as before.
Minor comments in order of appearance.
p. 2 ff it is politically critical to refer to the user always as he - I suggest she or s/he or he/she
p. 2 SKORecommender => SKOSRecommender
p. 3 [12, 13, 22, 24, 29, 50, 64] => are all these references necessary for such a minor point as made by this sentence?
p. 9 Table 6 reference should be Table 5 since this is the one showing the results of Q4
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