You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Patent retrieval: a literature review 
Chapter Title:  Patent litigation 
1. Abstract of Cited Paper (BIB001):  Sixteen years ago, two of us published the first detailed empirical look at patent litigation. In this Article, we update and expand the earlier study with a new hand-coded data set. We evaluate all substantive decisions rendered by any court in every patent case filed in 2008 and 2009 — decisions made between 2009 and 2013. We consider not just patent validity but also infringement and unenforceability. Moreover, we relate the outcomes of those cases to a host of variables, including variables related to the parties, the patents, and the courts in which those cases were litigated. The result is a comprehensive picture of the outcomes of modern patent litigation, one that confirms conventional wisdom in some respects but upends it in others. In particular, we find a surprising amount of continuity in the basic outcomes of patent lawsuits over the past twenty years, despite rather dramatic changes in who brought patent suits during that time. 
2. Abstract of Cited Paper (BIB002):  In this comprehensive new study, we evaluate all substantive decisions rendered by any court in every patent case filed in 2008 and 2009 — decisions made between 2009 and 2013. We assess the outcome of litigation by technology and industry. We relate the outcomes of those cases to a host of variables, including variables related to the parties, the patents, and the courts in which those cases were litigated. We find dramatic differences in the outcomes of patent litigation by both technology and industry. For example, owners of patents in the pharmaceutical industry fare much better in dispositive litigation rulings than do owners of patents in the computer & electronics industry, and chemistry patents have much greater success in litigation than their software or biotech counterparts. Our results provide an important window into both patent litigation and the industry-specific battles over patent reform. And they suggest that the traditional narrative of industry-specific patent disputes, which pits the IT industries against the life sciences, is incomplete. 
3. Abstract of Cited Paper (BIB003):  The legal profession appears to be on the brink of a major transformation, as new data analytics tools promise to revolutionize the ways lawyers practice law. One important aspect of this transformation is case forecasting -- that is, the way lawyers evaluate potential case outcomes. When a lawyer decides whether to initiate a new lawsuit, for example, or whether to settle an existing lawsuit, the lawyer must try to accurately assess the likely outcome of the case were it to proceed in litigation. This article examines the future role of data analytics in case forecasting, including its interplay with the method of predictive analysis lawyers have traditionally employed. This analysis has important implications not only for the practice of law, but also for legal pedagogy, which will need to conform to these expected changes in legal practice.

Literature Review:
Litigation in general, and patent litigation specifically, has been and still a topic of interest to legal professionals. With the increased amounts of digitized data available and the need for technology support in analyzing and mining these huge datasets, litigation became of more interest to computational science researchers. Patent litigation can take many forms, the most common is patent infringement litigation where a patent owner (plaintiff) accuses another party (defendant) of using his/her invention without license or permission. Because litigation is very expensive, the most common defensive action for the defendant is to establish invalidity of the plaintiff invention by issuing a post-grant proceeding such as post-grant review or interparts review. Now the problem becomes a patent retrieval task, i.e., invalidity search, where one of the aforementioned methods can be utilized with wider scope to cover not only the patent literature but also other published materials. The task of automatically establishing patent infringement is not addressed in the literature. Such task requires extensive human expertise and reasoning to build correspondences between product features and patent claims. On the other hand, statistical and visual analytics of previous court decisions have shown some degree of success in helping lawyers to better understand possible outcomes and better plan on defense strategies BIB002 BIB001 BIB004 . For example, Allison et al. BIB003 provided a statistical study on patent cases filed from 2008 to 2009 and decisions made between (2009 and 2013). The study showed that there is a strong correlation between court decision, and patent-specific, litigation-specific, and industry-specific variables such as industry and technology type, inventors foreign status, number of claims, number of forward and backward citations, and number of defendants sued. Rajshekhar et al.  studied the potential of concept-based semantic search in patent litigation. The authors designed an experiment in order to retrieve invalidating patents to a given litigated patent using a subset of PTAB's final decisions as ground truth and a search corpus of ∼7 m USPTO patents. The authors, based on the experimental results and through interviews with patent practitioners, concluded that a one-size-fits-all semantic search approach is incapable of capturing the highly nuanced relevance judgments made in the domain of patent litigation. Rather, the search workflow should be modeled as a multistage information seeking process, where users are presented with interactive elements to control the search space, and their feedback is incorporated iteratively in the relevance ranking of retrieved results for enhanced performance. Finally, There is much to be done in building predictive models for patent litigation given the availability of prior case datasets that were not available few years ago (e.g., prosecution histories, court decisions, and PTAB decisions).