Context preserving navigation redesign under Markovian assumption for responsive websites

- We model users' navigation behavior as a Markov process and represent it using a transition probability matrix.
- We define a metric called implied deviation to measure contextual relevance from designer's perspective.
- Propose deviation minimization framework to improve the contextual relevance from user as well as designer point of views.
- We provide note to practitioner which can help them identify potential of proposed framework better.
- Proposed framework is applied to two real access log data sets from a university examination website.

Identification and sorting of contextually relevant links are important for navigation design of responsive websites. While average click ratio is often used as a metric to evaluate contextual relevance of navigation structure from users' view, we propose a metric called implied deviation to quantify the same from designer point of view. Average click ratio minimization problem typically solved using meta-heuristics has issues such as loss of designer-defined contextual relevance and loss of connectivity among webpages. To solve this problem, we propose a deviation minimization framework to suggest context-preserving navigation structure. The proposed framework consists of three stages. Stage 1 models user navigation behavior as a Markov process and generates a transition probability matrix. Then we use the transition probabilities as weights to relax the original average click ratio minimization problem, and bring it to a form similar to a transportation model. The corresponding solution is considered as the initial basic feasible solution of the original problem. In Stage 2, transition probability guided meta-heuristics improve upon the initial basic feasible solution. Specifically, we use modified simulated annealing and ant colony optimization algorithms. This resulting solution is further weighted with transition probabilities to make a tradeoff in Stage 3. We obtained experimental results based on two education and university-related datasets to show that the proposed framework can achieve a good tradeoff for contextual relevance in terms of both the average click ratio and implied deviation.

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