Conceptual Visualization and Navigation Methods for Polyadic Formal Concept Analysis
Authors: Diana Troanca
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The goal of my thesis is to find visualization and navigation paradigms that can be applied to higher-dimensional datasets. Therefore, we study the triadic case and propose several visualization and navigational approaches. Furthermore, we evaluate these approaches, study their generalizations and extend them, where possible, to n-ary formal contexts. Both implementations were described in more detail, as well as evaluated and compared, in a paper currently under review. |
| Researcher Affiliation | Academia | Diana Troanc a Babes -Bolyai University Cluj-Napoca dianatt@cs.ubbcluj.ro Thesis Advisors: Prof. Sebastian Rudolph, sebastian.rudolph@tu-dresden.de, TU Dresden Prof. Florian-Mircea Boian, florin@cs.ubbcluj.ro, Babes -Bolyai University Cluj-Napoca |
| Pseudocode | No | The paper does not contain any pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | Yes | The first strategy1 relies on Answer Set Programming [Gebser et al., 2012] and extends the ASP encoding of the membership constraint satisfiability problem [Rudolph et al., 2015a].1 https://sourceforge.net/projects/asp-concept-navigation The second strategy2 is a brute force implementation and uses an exhaustive search in the whole formal concept space.2 https://sourceforge.net/projects/brute-force-concept-navigation |
| Open Datasets | No | In the following example we consider a triadic context where the object set consists of authors of scientific papers, the attribute set contains conference names/journal names while the conditions are the publication years (the data has been selected from dblp database). In our previous work we applied triadic FCA to study the navigational patterns of students in an e-learning environment [Dragos et al., 2014a; 2014b]. No specific links or citations are provided for public access to the DBLP data used in the example, or the e-learning environment data. |
| Dataset Splits | No | The paper discusses evaluation of approaches but does not provide specific details on dataset splits (e.g., train/validation/test percentages or counts) needed for reproduction. |
| Hardware Specification | No | The paper does not provide any specific hardware details (e.g., GPU/CPU models, memory, cloud instances) used for running experiments. |
| Software Dependencies | No | The paper mentions reliance on 'Answer Set Programming' and refers to 'Trias3 for the triadic case' (with a GitHub link provided for Trias), but it does not specify version numbers for these or any other ancillary software dependencies. |
| Experiment Setup | No | The paper describes the conceptual and algorithmic aspects of the proposed approaches but does not provide specific experimental setup details such as hyperparameter values, training configurations, or system-level settings. |