# US 2015/0149385 A1 · Visualization of reputation ratings > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2015/0149385 A1 - Document ID: US20150149385A1 - Status: Published application - Kind: A1 - Application number: 14/611,087 - Filed: 2015-01-30 - Published: 2015-05-28 - Earliest claimed: 2007-04-16 - Assignees: eBay Inc. - Applicants: eBay Inc. - Inventors: Neelakantan Sundaresan; Kavita Ganesan; Harshal Ulhas Deo - Web page: https://patentgrep.com/patent/US20150149385A1 ## CPC - G06Q 30/0282: Rating or review of business operators or products - G06F 16/00: Information retrieval; Database structures therefor; File system structures therefor - G06F 16/168: {Details of user interfaces specifically adapted to file systems, e.g. browsing and visualisation, 2d or 3d GUIs (query results presentation G06F16/156)} - G06F 16/248: Presentation of query results - G06F 16/26: Visual data mining; Browsing structured data - G06F 16/287: {Visualization; Browsing} - G06F 16/3323: {using document space presentation or visualization, e.g. category, hierarchy or range presentation and selection} - G06F 16/3326: {using relevance feedback from the user, e.g. relevance feedback on documents, documents sets, document terms or passages} - G06F 16/338: Presentation of query results - G06F 16/9535: Search customisation based on user profiles and personalisation - G06F 16/955: using information identifiers, e.g. uniform resource locators [URL] - G06F 16/958: Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking - G06F 40/30: Semantic analysis - G06Q 30/02: Marketing; Price estimation or determination; Fundraising - G06F 3/14: Digital output to display device {; Cooperation and interconnection of the display device with other functional units} - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract In one embodiment, a system and method is illustrated including receiving a feedback request identifying a particular user, retrieving a feedback entry in response to the feedback request, the feedback entry containing a first term, building a scoring model based, in part, upon a term frequency count denoting a frequency with which the first term appears in a searchable data structure, mapping the first term to a graphical illustration based upon a second term associated with the graphical illustration such that the graphical illustration may be used to represent the second term, and generating a feedback page containing the first term and the graphical illustration. The method may include assigning a value to the first term so as to identify the first term, assigning the first term to the searchable data structure, and extracting the first term from the searchable data structure based, in part, upon an extraction rule. ## Claims ### Claim 1 A system comprising: a first receiver configured to retrieve a plurality of feedback entries from a database, in response to a feedback request from a user selection at a user interface, a portion of the plurality of the feedback entries containing a first phrase; a score builder configured to determine, by a frequency engine using one or more processors, a frequency score based on a frequency count for the first phrase of each of the retrieved feedback entries; a mapping engine configured to map, using one or more processors, the first phrase to a visual indication, the mapping based upon a second phrase associated with the visual indication; and a page generator configured to generate a user interface depicting a feedback page containing the first phrase and the visual indication. ### Claim 2 (depends on 1) The system of claim 1, wherein the feedback request includes an identifier of a particular product. ### Claim 3 (depends on 1) The system of claim 1, wherein the frequency count for each phrase is based on an aggregation of a frequency count of each word within the phrase. ### Claim 4 (depends on 1) The system of claim 1, further comprising: a filter configured to filter noise words from the plurality of feedback entries, the filtering based upon the plurality of feedback entries associated with a dictionary of noise words; the mapping engine configured to map, using one or more processor, the filtered terms based on a searchable data structure to a visual indication, the searchable data structure containing positive, neutral, or negative feedback entries; and the page generator configured to generate a feedback page, in response to the feedback request, containing the filtered terms and the visual indication. ### Claim 5 (depends on 1) The system of claim 1, further comprising: a first assigner configured to assign a value to the first term so as to identify the first term; a second assigner configured to assign the first term to the searchable data structure; and a term extractor configured to extract the first term from the searchable data structure based, in part, upon an extraction rule. ### Claim 6 (depends on 1) The system of claim 1, further comprising a highlighter engine configured to highlight the first term based upon a score related to the frequency score, the score being a product of the term frequency count and an inverse document frequency value. ### Claim 7 (depends on 6) The system of claim 6, wherein the first term is part of at least one of a group consisting of category level context, a global level context, a static domain level context, and a dynamic domain context. ### Claim 8 (depends on 6) The system of claim 6, further comprising the highlighter engine using a highlight including at least one of a group of highlights consisting of font size highlight, a color highlight, a underline highlights, and a bold highlight. ### Claim 9 (depends on 1) The system of claim 1, wherein the searchable data structure is at least one of a group consisting of trie, hash table, red-black tree, and Binary Search Tree (BST). ### Claim 10 (depends on 1) The system of claim 1, wherein the visual indication is an emoticon. ### Claim 11 A method comprising: retrieving a plurality of feedback entries from a database, in response to a feedback request from a user selection at a user interface, a portion of the plurality of the feedback entries containing a first phrase, each retrieved feedback entry being about a transaction; determining, by a frequency engine using one or more processors, a frequency score based on a frequency count for the first phrase of each of the retrieved feedback entries; mapping, using one or more processors, the first phrase to a visual indication, the mapping based upon a second phrase associated with the visual indication; and generating a user interface depicting a feedback page containing the first phrase and the visual indication. ### Claim 12 (depends on 11) The method of claim 11, wherein the feedback request includes an identifier of a particular product. ### Claim 13 (depends on 11) The method of claim 11, wherein the frequency count for each phrase is based on an aggregation of a frequency count of each word within the phrase. ### Claim 14 (depends on 11) The method of claim 11, further comprising: filtering noise words from the plurality of feedback entries, the filtering based upon the plurality of feedback entries associated with a dictionary of noise words; mapping, using one or more processor, the filtered terms based on a searchable data structure to a visual indication, the searchable data structure containing positive, neutral, or negative feedback entries; and generating a feedback page, in response to the feedback request, containing the filtered terms and the visual indication. ### Claim 15 (depends on 11) The method of claim 11, further comprising: assigning a value to the first term so as to identify the first term; assigning the first term to the searchable data structure; and extracting the first term from the searchable data structure based, in part, upon an extraction rule. ### Claim 16 (depends on 11) The method of claim 11, further comprising highlighting the first term based upon a score related to the frequency score, the score being a product of the term frequency count and an inverse document frequency value. ### Claim 17 (depends on 16) The method of claim 16, wherein the first term is part of at least one of a group consisting of category level context, a global level context, a static domain level context, and a dynamic domain context. ### Claim 18 (depends on 16) The method of claim 16, further comprising using a highlight including at least one of a group of highlights consisting of font size highlight, a color highlight, a underline highlights, and a bold highlight. ### Claim 19 (depends on 11) The method of claim 11, wherein the searchable data structure is at least one of a group consisting of trie, hash table, red-black tree, and Binary Search Tree (BST). ### Claim 20 A non-transitory machine-readable storage medium comprising instructions, which when implemented by one or more machines, cause the one or more machines to perform operations comprising: retrieving a plurality of feedback entries from a database, in response to a feedback request from a user selection at a user interface, a portion of the plurality of the feedback entries containing a first phrase, each retrieved feedback entry being about a transaction; determining, by a frequency engine using one or more processors, a frequency score based on a frequency count for the first phrase of each of the retrieved feedback entries; mapping, using one or more processors, the first phrase to a visual indication, the mapping based upon a second phrase associated with the visual indication; and generating a user interface depicting a feedback page containing the first phrase and the visual indication.