On Term Selection Techniques for Patent Prior Art Search

A patent is a set of exclusive rights granted to an inventor to protect his invention for a limited period of time. Patent prior art search involves finding previously granted patents, scientific articles, product descriptions, or any other published work that may be relevant to a new patent application. Many well-known information retrieval (IR) techniques (e.g., typical query expansion methods), which are proven effective for ad hoc search, are unsuccessful for patent prior art search. In this thesis, we mainly investigate the reasons that generic IR techniques are not effective for prior art search on the CLEF-IP test collection. First, we analyse the errors caused due to data curation and experimental settings like applying International Patent Classification codes assigned to the patent topics to filter the search results. Then, we investigate the influence of term selection on retrieval performance on the CLEF-IP prior art test collection, starting with the description section of the reference patent and using language models (LM) and BM25 scoring functions. We find that an oracular relevance feedback system, which extracts terms from the judged relevant documents far outperforms the baseline (i.e., 0.11 vs. 0.48) and performs twice as well on mean average precision (MAP) as the best participant in CLEF-IP 2010 (i.e., 0.22 vs. 0.48). We find a very clear term selection value threshold for use when choosing terms. We also notice that most of the useful feedback terms are actually present in the original query and hypothesise that the baseline system can be substantially improved by removing negative query terms. We try four simple automated approaches to identify negative terms for query reduction but we are unable to improve on the baseline performance with any of them. However, we show that a simple, minimal feedback interactive approach, where terms are selected from only the first retrieved relevant document outperforms the best result from CLEF-IP 2010, suggesting the promise of interactive methods for term selection in patent prior art search

A study of query expansion methods for patent retrieval

Patent retrieval is a recall-oriented search task where the objective is to find all possible relevant documents. Queries in patent retrieval are typically very long since they take the form of a patent claim or even a full patent application in the case of priorart patent search. Nevertheless, there is generally a significant mismatch between the query and the relevant documents, often leading to low retrieval effectiveness. Some previous work has tried to address this mismatch through the application of query expansion (QE) techniques which have generally showed effectiveness for many other retrieval tasks. However, results of QE on patent search have been found to be very disappointing. We present a review of previous investigations of QE in patent retrieval, and explore some of these techniques on a prior-art patent search task. In addition, a novel method for QE using automatically generated synonyms set is presented. While previous QE techniques fail to improve over baseline retrieval, our new approach show statistically better retrieval precision over the baseline, although not for recall. In addition, it proves to be significantly more efficient than existing techniques. An extensive analysis to the results is presented which seeks to better understand situations where these QE techniques succeed or fail

Multiple Retrieval Models and Regression Models for Prior Art Search

This paper presents the system called PATATRAS (PATent and Article Tracking, Retrieval and AnalysiS) realized for the IP track of CLEF 2009. Our approach presents three main characteristics: 1. The usage of multiple retrieval models (KL, Okapi) and term index definitions (lemma, phrase, concept) for the three languages considered in the present track (English, French, German) producing ten different sets of ranked results. 2. The merging of the different results based on multiple regression models using an additional validation set created from the patent collection. 3. The exploitation of patent metadata and of the citation structures for creating restricted initial working sets of patents and for producing a final re-ranking regression model. As we exploit specific metadata of the patent documents and the citation relations only at the creation of initial working sets and during the final post ranking step, our architecture remains generic and easy to extend

Utilizing sub-topical structure of documents for information retrieval.

Text segmentation in natural language processing typically refers to the process of decomposing a document into constituent subtopics. Our work centers on the application of text segmentation techniques within information retrieval (IR) tasks. For example, for scoring a document by combining the retrieval scores of its constituent segments, exploiting the proximity of query terms in documents for ad-hoc search, and for question answering (QA), where retrieved passages from multiple documents are aggregated and presented as a single document to a searcher. Feedback in ad hoc IR task is shown to benefit from the use of extracted sentences instead of terms from the pseudo relevant documents for query expansion. Retrieval effectiveness for patent prior art search task is enhanced by applying text segmentation to the patent queries. Another aspect of our work involves augmenting text segmentation techniques to produce segments which are more readable with less unresolved anaphora. This is particularly useful for QA and snippet generation tasks where the objective is to aggregate relevant and novel information from multiple documents satisfying user information need on one hand, and ensuring that the automatically generated content presented to the user is easily readable without reference to the original source document

Reply With: Proactive Recommendation of Email Attachments

Email responses often contain items-such as a file or a hyperlink to an external document-that are attached to or included inline in the body of the message. Analysis of an enterprise email corpus reveals that 35% of the time when users include these items as part of their response, the attachable item is already present in their inbox or sent folder. A modern email client can proactively retrieve relevant attachable items from the user's past emails based on the context of the current conversation, and recommend them for inclusion, to reduce the time and effort involved in composing the response. In this paper, we propose a weakly supervised learning framework for recommending attachable items to the user. As email search systems are commonly available, we constrain the recommendation task to formulating effective search queries from the context of the conversations. The query is submitted to an existing IR system to retrieve relevant items for attachment. We also present a novel strategy for generating labels from an email corpus---without the need for manual annotations---that can be used to train and evaluate the query formulation model. In addition, we describe a deep convolutional neural network that demonstrates satisfactory performance on this query formulation task when evaluated on the publicly available Avocado dataset and a proprietary dataset of internal emails obtained through an employee participation program.Comment: CIKM2017. Proceedings of the 26th ACM International Conference on Information and Knowledge Management. 201

The course of lectures on discipline “Intellectual property” (for the 5 year students of the specialty 8.03060101 “Management”)

Затверджено на засіданні кафедри менеджменту інноваційної діяльності та підприємнцтва. Протокол No 1 від 27 серпня 2015 р. Рекомендовано методичною комісією факультету управління і бізнесу у виробництві ТНТУ імені Івана Пулюя. Протокол No 6 від 26 лютого 2016 р.У методичних вказівках, у відповідності до робочої програми, сформовано лекційний матеріал з дисципліни “Інтелектуальна власність” для іноземних студентів спеціальності 8.03060101 “Менеджмент організацій та адміністрування”.Методичні вказівки призначені для допомоги іноземним студентам при вивченні курсу “Інтелектуальна власність”. У методичних вказівках містяться загальні теоретичні відомості, необхідні до вивчення даного курсу. Рекомендовано для іноземних студентів спеціальності 8.03060101 “Менеджмент організацій та адміністрування” з метою закріплення, поглиблення і узагальнення знань, одержаних студентами за час навчання та їх застосування до комплексного вирішення конкретного фахового завдання із дисципліни “Інтелектуальна власність”. Складено з урахуванням робочої програми вивчення курсу, методичних розробок інших вузів, а також матеріалів літературних джерел, наведених у рекомендованій літературі

How Courts Adjudicate Patent Definiteness and Disclosure

Section 112 of the Patent Act requires patentees to clearly explain what their invention is (a requirement known as claim definiteness), as well as how to make and use it (the disclosure requirements of enablement and written description). Many concerns about the modern patent system stem from these requirements. But despite the critical importance of § 112 to the functioning of the patent system, there is surprisingly little empirical data about how it has been applied in practice. To remedy the reliance on anecdotes, we have created a hand-coded dataset of 1144 reported court decisions from 1982 to 2012 in which U.S. district courts or the Court of Appeals for the Federal Circuit rendered a decision on the enablement, written-description, or claim-definiteness requirements of § 112. We coded validity outcomes under these three doctrines on a novel five-level scale so as to capture significant subtlety in the strength of each decision, and we also classified patents by technology and industry categories. We also coded for a number of litigation characteristics that could arguably influence outcomes. Although one must be cautious about generalizing from reported decisions due to selection effects, our results show some statistically significant disparities in § 112 outcomes for different technologies and industries—although fewer than the conventional wisdom suggests, and not always in the direction that many have believed. Just as importantly, our analysis reveals significant relationships between other variables and § 112 litigation outcomes, including whether a district court or the Federal Circuit made the last decision in a case, whether a patent claim was drafted in means-plus-function format, and whether a case was decided before or after Markman v. Westview Instruments. Our results showing how § 112 has been applied in practice will be helpful in evaluating current proposals for reform, and our rich dataset will enable more systematic studies of these critical doctrines in the future

Business Method Patents in Europe and their Strategic Use - Evidence from Franking Device Manufacturers

There has been a wide-spread misconception based on the imprecise wording of Art. 52 of the European Patent Convention (EPC) that the protection of business methods by patents is prohibited in Europe. This paper investigates the legal framework set by patent laws with respect to the patentability of business methods, contrasting the situation in lege in Europe and the situation in the US. It is shown that in praxi business methods have never been excluded from patentability in Europe. In the empirical part of the paper, 1,901 European patent applications relating to business methods are identified and major patent indicators are computed. Further, a case study from the franking device industry which is characterized by strong competition for intellectual property rights is conducted. It contains evidence for the strategic use of business method patents leading to opposition rates against granted patents of 44%

High temperature solder device for flat cables

A high temperature solder device for flat cables includes a microwelder, an anvil which acts as a heat sink and supports a flexible flat ribbon cable that is to be connected to a multiple pin connector. The microwelder is made from a modified commercially available resistance welding machine such as the Split Tip Electrode microwelder by Weltek, which consists of two separate electrode halves with a removable dielectric spacer in between. The microwelder is not used to weld the items together, but to provide a controlled compressive force on, and energy pulse to, a solder preform placed between a pin of the connector and a conductor of the flexible flat ribbon cable. When the microwelder is operated, an electric pulse will flow down one electrode, through the solder preform and back up the other electrode. This pulse of electrical energy will cause the solder preform to heat up and melt, joining the pin and conductor