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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