AcclaimIP supports about 48 fields of exportable data for each patent. The number of rows that can be exported each time will vary depending on the plan you choose. Analyst users can export up to 50,000 rows of patent data per export. The format is csv by default, but AcclaimIP also supports native Excel (xls). In some instances the number of rows you can export may be limited when you choose the xls option.
MLT stands for ‘More Like This.’ It is a linguistic technique for finding similar documents based on the context of their text. MLT can be accessed from the Tools>Similar Documents menu on the Documents Details window or from the Natural Language tab in the Advanced Search window.
Meta data is defined as data about data. In AcclaimIP’s case, we compute over 20 different values about each patent that cannot in itself be found in the patent data when we receive them from the various PTOs. For example, we compute many counts such as number of claims, days in prosecution, number of forward citations, number of inventors. Each meta data element can be found in its own column in the search result grids. Each search result can be sorted by those columns.
Document Clustering is a technique that can bucketize or carve up a large set of patent documents into logical themes. We support document clustering. The size of the cluster varies with the membership level. Our clustering is done in near real time. For example it takes about 5 seconds to cluster 500 patents. Many earlier systems would take from 20 minutes to overnight to cluster a similar size document set.
QueryFlow is a tool that analyses one patent, or a group of patents for “important” keywords and terms. Important terms are terms that are found relatively often in the source patent or patents, but occur relatively rarely in the entire corpus of patent documents. As a result, QueryFlow identifies which terms are the most effective for identifying patents similar to the patent or patents you selected.
QueryFlow further lets you edit the terms it chooses, change their weightings, and execute queries directly from a easy-to-use grid of terms. You don’t need to worry about your syntax when constructing complex keyword queries with QueryFlow.
Class profiling is a technology build into AcclaimIP that finds similar patents to any target patent using a profiling matrix based on the original and cross reference classifications of the target patent. It is unique to AcclaimIP since it is the only software package on the market that is aware of the class hierarchy and the parent child relationship of each class for US, CPC and IPC classifications systems. Users find that class profiling works at least as well as semantically identifying similar patents, but has the unique advantage of being completely independent of the patent author’s vocabulary, word choice and lexicon.
Query matrices are a tool that allows you to create hundreds or thousands of cross referenced queries and execute them at the same time. It is the only legitimate tool that can adequately landscape any patent technology across all the relevant competitors in your market and stay up to date each week as new patents and applications are released.