Caching is one technique that reduces costs and improves performance in mobile environments. It also increases availability during temporary, involuntary disconnections. However, our focus is on voluntary, client initiated disconnections, where hoarding can be used to predict data requirements. Existing hoarding approaches ignore conflicts arising out of write sharing and are thus unable to deal with them. However, since conflicts are detrimental to bandwidth utilisation, for scenarios with high write sharing, hoarding techniques need to provide support for sharing in a manner that reduces or avoids conflicts. We propose a hoarding approach for disconnected write operations that focuses on reducing the likelihood of conflicts, arising from write sharing, in a highly concurrent environment. Data that clients might need when disconnected is predicted based on the notion of semantic similarity. To avoid/reduce conflicts, data are first clustered based on their update probabilities. The hoard tree is then created based on the clusters and semantic similarity between data. Simulations show an increase in the cache hit-rate along with an reduction in the total number of conflicts.