[Context　and　motivation]　In　the　increasingly　competitive　software　market,　it　is　essential　for　software　companies　to　have　a　comprehensive　understanding　of　development　progress　and　user　preferences　of　their　corresponding　application　domain.　[Question/problem]　However,　given　the　huge　number　of　existing　software　applications,　it　is　impossible　to　gain　such　insights　via　manual　inspection.　[Principal　ideas/results]　In　this　paper,　we　present　a　research　preview　of　automatic　user　preferences　elicitation　approach.　Specifically,　our　approach　first　clusters　software　applications　into　different　categories　based　on　their　descriptions,　and　then　identifies　features　of　each　category.　We　then　link　such　features　to　corresponding　user　reviews　and　automatically　classify　sentiments　of　each　review　In　order　to　understand　user　preferences　over　such　feature　In　addition,　we　have　carefully　planned　evaluations　that　will　be　carried　out　to　further　polish　our　work.　[Contributions]　Our　proposal　aims　to　help　software　companies　to　identify　features　of　applications　in　a　particular　domain,　as　well　as　user　preferences　with　regard　to　those　features.　We　argue　such　analysis　is　especially　important　for　startup　companies　that　have　few　knowledge　about　the　domain.