Annually, web search engine providers spend more and more money on documents ranking in search engines result pages (SERP). Click models provide advantageous information for ranking documents in SERPs through modeling interactions among users and search engines. Here, three modules are employed to create a hybrid click model; the first module is a PGM-based click model, the second module in a d...

In this paper, we develop and evaluate several probabilistic models of user click-through behavior that are appropriate for modeling the click-through rates of items that are presented to the user in a list. Potential applications include modeling the click-through rates of search results from a search engine, items ranked by a recommendation system, and search advertisements returned by a sear...

A fundamental problem in sponsored search advertising is the estimation of probability of click for ads displayed in response to search queries. The historical click-through rate (CTR) is one of the most important predictors of the click, and extracted at multiple resolutions of the query-ad hierarchy. However, the new ads do not have any click history, and even the existing ads might miss hist...

A series of metallosupramolecular [Fe₂L₃](BF₄)₄ "click" cylinders have been synthesized in excellent yields (90%-95%) from [Fe(H₂O)₆](BF₄)₂ and bis(bidentate) pyridyl-1,2,3-triazole ligands. All complexes were characterized by elemental analysis, IR, UV-vis, ¹H-, ¹³C- and DOSY-NMR spectroscopies and, in four cases, the structures confirmed by X-ray crystallography. Molecular modeling indicated ...

Contextual data plays an important role in modeling search engine users’ behaviors on both query auto-completion (QAC) log and normal query (click) log. User’s recent search history on each log has been widely studied individually as the context to benefit the modeling of users’ behaviors on that log. However, there is no existing work that explores or incorporates both logs together for contex...

We propose methods for estimating the probability that an entity from an entity database is associated with a web search query. Association is modeled using a query entity click graph, blending general query click logs with vertical query click logs. Smoothing techniques are proposed to address the inherent data sparsity in such graphs, including interpolation using a query synonymy model. A la...

Understanding user browsing behavior in web search is key to improving web search effectiveness. Many click models have been proposed to explain or predict user clicks on search engine results. They are based on the probabilistic graphical model (PGM) framework, in which user behavior is represented as a sequence of observable and hidden events. The PGM framework provides a mathematically solid...